speech_recognition.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "speech_recognition.ipynb",
      "provenance": [],
      "collapsed_sections": [
        "diuZbXxB6i0A",
        "be0tgsepiNNg"
      ]
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU",
    "widgets": {
      "application/vnd.jupyter.widget-state+json": {
        "0d1e0cc4415e4fcfb0c7d25e9367debd": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HBoxView",
            "_dom_classes": [],
            "_model_name": "HBoxModel",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "box_style": "",
            "layout": "IPY_MODEL_e36e782b71d1498cb496046952d4eec5",
            "_model_module": "@jupyter-widgets/controls",
            "children": [
              "IPY_MODEL_403e8036e011443f9f08bcfe64618d29",
              "IPY_MODEL_4273da32cd9a49b3ae700fb3d6fbedd0",
              "IPY_MODEL_d8f638cdf3dd4c5497cb05a8a0fb7ad0"
            ]
          }
        },
        "e36e782b71d1498cb496046952d4eec5": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "403e8036e011443f9f08bcfe64618d29": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_a89873d4c2184e01adaa511d352f6bb5",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": "Dl Completed...: 100%",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_38a2092df6db406db8be09169b8109cd"
          }
        },
        "4273da32cd9a49b3ae700fb3d6fbedd0": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "ProgressView",
            "style": "IPY_MODEL_3d7d5e1359754bafaf9446af91037330",
            "_dom_classes": [],
            "description": "",
            "_model_name": "FloatProgressModel",
            "bar_style": "success",
            "max": 1,
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": 1,
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "orientation": "horizontal",
            "min": 0,
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_7a586561029440a09a6e5ecd92228195"
          }
        },
        "d8f638cdf3dd4c5497cb05a8a0fb7ad0": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_70f789b7efc043a2bd905cd3b9edd0a7",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": " 2/2 [00:44&lt;00:00, 25.08s/ url]",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_ab13cb424ba54b678428e144cac7775a"
          }
        },
        "a89873d4c2184e01adaa511d352f6bb5": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "38a2092df6db406db8be09169b8109cd": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "3d7d5e1359754bafaf9446af91037330": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "ProgressStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "bar_color": null,
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "7a586561029440a09a6e5ecd92228195": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": "20px",
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "70f789b7efc043a2bd905cd3b9edd0a7": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "ab13cb424ba54b678428e144cac7775a": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "42b4f020ae3049319466539b5923cffc": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HBoxView",
            "_dom_classes": [],
            "_model_name": "HBoxModel",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "box_style": "",
            "layout": "IPY_MODEL_ab6f7a1b22a3424cb2b381804bc05751",
            "_model_module": "@jupyter-widgets/controls",
            "children": [
              "IPY_MODEL_115ba5781eed486799054a89c6ff95d1",
              "IPY_MODEL_c537623134d94e1ea55a676ee3271f0b",
              "IPY_MODEL_65d260cec9aa44029ef3b0923a2b1e39"
            ]
          }
        },
        "ab6f7a1b22a3424cb2b381804bc05751": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "115ba5781eed486799054a89c6ff95d1": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_5036862f720e465a8634e2ff4f2cee9c",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": "Dl Size...: 100%",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_5676bbba7e4547f9ac1cf0779ad472d2"
          }
        },
        "c537623134d94e1ea55a676ee3271f0b": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "ProgressView",
            "style": "IPY_MODEL_3369732b9149422d80566f4fbc8db7b0",
            "_dom_classes": [],
            "description": "",
            "_model_name": "FloatProgressModel",
            "bar_style": "success",
            "max": 1,
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": 1,
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "orientation": "horizontal",
            "min": 0,
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_47e79578e3ec407fa7eade747fedec77"
          }
        },
        "65d260cec9aa44029ef3b0923a2b1e39": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_082f381ba40f4762803f369f054cc987",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": " 2423/2423 [00:44&lt;00:00, 56.11 MiB/s]",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_7606ff9d1fae4a1d9014b43a61004404"
          }
        },
        "5036862f720e465a8634e2ff4f2cee9c": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "5676bbba7e4547f9ac1cf0779ad472d2": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "3369732b9149422d80566f4fbc8db7b0": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "ProgressStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "bar_color": null,
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "47e79578e3ec407fa7eade747fedec77": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": "20px",
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "082f381ba40f4762803f369f054cc987": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "7606ff9d1fae4a1d9014b43a61004404": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "f12b385712c3492b99ea12d9795483d2": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HBoxView",
            "_dom_classes": [],
            "_model_name": "HBoxModel",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "box_style": "",
            "layout": "IPY_MODEL_ba8e627c2a2249768b81450193bbb919",
            "_model_module": "@jupyter-widgets/controls",
            "children": [
              "IPY_MODEL_72e0b17f6ca442b784bc635112a2416f",
              "IPY_MODEL_82a570256dc34d76a7fbf56524d0f3d5",
              "IPY_MODEL_be15ddece2584426a92ad313c5eb779a"
            ]
          }
        },
        "ba8e627c2a2249768b81450193bbb919": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "72e0b17f6ca442b784bc635112a2416f": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_df4c61bdd443427fac6693cabc1b0e76",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": "",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_cb77715818bd4be781aa9cafb5f7ac62"
          }
        },
        "82a570256dc34d76a7fbf56524d0f3d5": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "ProgressView",
            "style": "IPY_MODEL_1126c99c48ed4c54a42df9e62f1a8b4c",
            "_dom_classes": [],
            "description": "",
            "_model_name": "FloatProgressModel",
            "bar_style": "info",
            "max": 1,
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": 1,
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "orientation": "horizontal",
            "min": 0,
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_b1a916d2ae1842cd9f42e37f4c4cd7c7"
          }
        },
        "be15ddece2584426a92ad313c5eb779a": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_4afdd666bcca43b0ade8d8b714686639",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": " 85499/0 [09:28&lt;00:00, 153.98 examples/s]",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_ef6b78adc5994a9696f70a6689555268"
          }
        },
        "df4c61bdd443427fac6693cabc1b0e76": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "cb77715818bd4be781aa9cafb5f7ac62": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "1126c99c48ed4c54a42df9e62f1a8b4c": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "ProgressStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "bar_color": null,
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "b1a916d2ae1842cd9f42e37f4c4cd7c7": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": "20px",
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "4afdd666bcca43b0ade8d8b714686639": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "ef6b78adc5994a9696f70a6689555268": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "a1f6c525c69e4d9282714a6be9d048c1": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HBoxView",
            "_dom_classes": [],
            "_model_name": "HBoxModel",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "box_style": "",
            "layout": "IPY_MODEL_48fc22d8eab042f3937afd92911d3767",
            "_model_module": "@jupyter-widgets/controls",
            "children": [
              "IPY_MODEL_df1fac49d5d045c09df74677a397dde2",
              "IPY_MODEL_cb44cdac87d94b1eac5ec8b17a989c31",
              "IPY_MODEL_3e8892ad45cc4a44b0fb527c7be56c7d"
            ]
          }
        },
        "48fc22d8eab042f3937afd92911d3767": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "df1fac49d5d045c09df74677a397dde2": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_650127bf9679430bbbade80ecf33d2b6",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": "100%",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_b02f05313faa42569416ae4c3bdc2b00"
          }
        },
        "cb44cdac87d94b1eac5ec8b17a989c31": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "ProgressView",
            "style": "IPY_MODEL_9eef7276fab14f6d95a30f96fe09f9f3",
            "_dom_classes": [],
            "description": "",
            "_model_name": "FloatProgressModel",
            "bar_style": "danger",
            "max": 85511,
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": 85510,
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "orientation": "horizontal",
            "min": 0,
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_87d414b67437424a88ea870a04f2c311"
          }
        },
        "3e8892ad45cc4a44b0fb527c7be56c7d": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_08e2daa05c02493fb23b6f22afee9934",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": " 85510/85511 [02:20&lt;00:00, 1431.85 examples/s]",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_05f1416828b8497ea9887c1bed261d20"
          }
        },
        "650127bf9679430bbbade80ecf33d2b6": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "b02f05313faa42569416ae4c3bdc2b00": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "9eef7276fab14f6d95a30f96fe09f9f3": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "ProgressStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "bar_color": null,
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "87d414b67437424a88ea870a04f2c311": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "08e2daa05c02493fb23b6f22afee9934": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "05f1416828b8497ea9887c1bed261d20": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "1ccbdef9fe934b5b90d193dfdce9fe33": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HBoxView",
            "_dom_classes": [],
            "_model_name": "HBoxModel",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "box_style": "",
            "layout": "IPY_MODEL_2e792dcb3b9c4b37b943f7d48bfe1f47",
            "_model_module": "@jupyter-widgets/controls",
            "children": [
              "IPY_MODEL_92988901f8db4863b99a36e980246686",
              "IPY_MODEL_8201474ddf17463eb39311e00d2d01c8",
              "IPY_MODEL_32c9f9fdb7aa49838dd9001e7a51980b"
            ]
          }
        },
        "2e792dcb3b9c4b37b943f7d48bfe1f47": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "92988901f8db4863b99a36e980246686": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_582a01c96fc7485da551d2c1fe68e72a",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": "",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_72db5e3aaa00422e984c6c96594610aa"
          }
        },
        "8201474ddf17463eb39311e00d2d01c8": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "ProgressView",
            "style": "IPY_MODEL_c4eabbcc50b145679d4cf862aff34476",
            "_dom_classes": [],
            "description": "",
            "_model_name": "FloatProgressModel",
            "bar_style": "info",
            "max": 1,
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": 1,
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "orientation": "horizontal",
            "min": 0,
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_7dce796c099543ec88b20a62a1b92ef2"
          }
        },
        "32c9f9fdb7aa49838dd9001e7a51980b": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_26baa2b121854d91a4b3d60353579ae1",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": " 10097/0 [02:07&lt;00:00, 73.13 examples/s]",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_5701351a577d4c788a42f72d8f19b33b"
          }
        },
        "582a01c96fc7485da551d2c1fe68e72a": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "72db5e3aaa00422e984c6c96594610aa": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "c4eabbcc50b145679d4cf862aff34476": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "ProgressStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "bar_color": null,
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "7dce796c099543ec88b20a62a1b92ef2": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": "20px",
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "26baa2b121854d91a4b3d60353579ae1": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "5701351a577d4c788a42f72d8f19b33b": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "21ed5f6ed72146199b23c2f602ef8279": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HBoxView",
            "_dom_classes": [],
            "_model_name": "HBoxModel",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "box_style": "",
            "layout": "IPY_MODEL_7405f4b6e9a34fe38330dbc713c30ef5",
            "_model_module": "@jupyter-widgets/controls",
            "children": [
              "IPY_MODEL_152c72c8d9d14f928794484d9f46ad03",
              "IPY_MODEL_90de478c64894473a07531da446e3700",
              "IPY_MODEL_f28ebbf31972465dabfd5f768577b2d4"
            ]
          }
        },
        "7405f4b6e9a34fe38330dbc713c30ef5": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "152c72c8d9d14f928794484d9f46ad03": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_e0f06924177e4d2ab42dd20bc9c32148",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": "100%",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_02f990ddbe864d4da39f5f8149993292"
          }
        },
        "90de478c64894473a07531da446e3700": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "ProgressView",
            "style": "IPY_MODEL_8b1df2c884b44edda758a1172697601a",
            "_dom_classes": [],
            "description": "",
            "_model_name": "FloatProgressModel",
            "bar_style": "danger",
            "max": 10102,
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": 10101,
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "orientation": "horizontal",
            "min": 0,
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_e7ccd2b99fd340b6b1b51c688ae81728"
          }
        },
        "f28ebbf31972465dabfd5f768577b2d4": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_e925e9563d794cadbea985c038421f53",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": " 10101/10102 [00:02&lt;00:00, 2827.83 examples/s]",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_9afc5e4fa3774f08b35cc815cc665ef7"
          }
        },
        "e0f06924177e4d2ab42dd20bc9c32148": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "02f990ddbe864d4da39f5f8149993292": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "8b1df2c884b44edda758a1172697601a": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "ProgressStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "bar_color": null,
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "e7ccd2b99fd340b6b1b51c688ae81728": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "e925e9563d794cadbea985c038421f53": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "9afc5e4fa3774f08b35cc815cc665ef7": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "b36d78e8817645b292ff128ef86b3f5c": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HBoxView",
            "_dom_classes": [],
            "_model_name": "HBoxModel",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "box_style": "",
            "layout": "IPY_MODEL_f79d7326371248c5bb0f731e2b4f4a15",
            "_model_module": "@jupyter-widgets/controls",
            "children": [
              "IPY_MODEL_87e23f3b24bf42a4b649e741752ad96c",
              "IPY_MODEL_4c42c073d17840c8af1d268622f58722",
              "IPY_MODEL_680ce27788ed47559ccbb74fb1b41e46"
            ]
          }
        },
        "f79d7326371248c5bb0f731e2b4f4a15": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "87e23f3b24bf42a4b649e741752ad96c": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_7bc834feca1f45328ee5ac09fa12fe52",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": "",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_39687c8c6e2f41fd8f072dc8822fe579"
          }
        },
        "4c42c073d17840c8af1d268622f58722": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "ProgressView",
            "style": "IPY_MODEL_adc52c96e75146ddbe9be02b137d090b",
            "_dom_classes": [],
            "description": "",
            "_model_name": "FloatProgressModel",
            "bar_style": "info",
            "max": 1,
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": 1,
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "orientation": "horizontal",
            "min": 0,
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_77fe1cd73c924f23874607c0f6ea02b3"
          }
        },
        "680ce27788ed47559ccbb74fb1b41e46": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_2cf5d74e292b4b5ba44e2d64aee66276",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": " 4890/0 [00:33&lt;00:00, 154.79 examples/s]",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_9f177d751e9f4ca5912ab376112e84af"
          }
        },
        "7bc834feca1f45328ee5ac09fa12fe52": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "39687c8c6e2f41fd8f072dc8822fe579": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "adc52c96e75146ddbe9be02b137d090b": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "ProgressStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "bar_color": null,
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "77fe1cd73c924f23874607c0f6ea02b3": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": "20px",
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "2cf5d74e292b4b5ba44e2d64aee66276": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "9f177d751e9f4ca5912ab376112e84af": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "d99f40914acd40f9bbdb4c75dfd266f4": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HBoxView",
            "_dom_classes": [],
            "_model_name": "HBoxModel",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "box_style": "",
            "layout": "IPY_MODEL_288f79a7a6aa48fa9905203ccc53f0a0",
            "_model_module": "@jupyter-widgets/controls",
            "children": [
              "IPY_MODEL_ea26d0c8fdc04114890f673c9d618c39",
              "IPY_MODEL_926c53d1bea54f1c958eb1623de9f5eb",
              "IPY_MODEL_28b7920d953841c998fc535552ebc430"
            ]
          }
        },
        "288f79a7a6aa48fa9905203ccc53f0a0": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "ea26d0c8fdc04114890f673c9d618c39": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_1763a9e63423494cb26bd7057cdd1100",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": "100%",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_8502621448a74334b75c82cdf87328bb"
          }
        },
        "926c53d1bea54f1c958eb1623de9f5eb": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "ProgressView",
            "style": "IPY_MODEL_6ea7524019344be3a37a519a699589c4",
            "_dom_classes": [],
            "description": "",
            "_model_name": "FloatProgressModel",
            "bar_style": "danger",
            "max": 4890,
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": 4889,
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "orientation": "horizontal",
            "min": 0,
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_efccef0040b24b488993779905fa145e"
          }
        },
        "28b7920d953841c998fc535552ebc430": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_169d9d2cc5d148969c484fbb8d507064",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": " 4889/4890 [00:01&lt;00:00, 3065.57 examples/s]",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_4208d65f74f640b1bea63f68b77d2fed"
          }
        },
        "1763a9e63423494cb26bd7057cdd1100": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "8502621448a74334b75c82cdf87328bb": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "6ea7524019344be3a37a519a699589c4": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "ProgressStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "bar_color": null,
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "efccef0040b24b488993779905fa145e": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "169d9d2cc5d148969c484fbb8d507064": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "4208d65f74f640b1bea63f68b77d2fed": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        }
      }
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "# Imports"
      ],
      "metadata": {
        "id": "2-3K2CKr6fP3"
      }
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KE0JjJhC0UQr",
        "outputId": "1239c3d8-937f-4c8f-a136-edbffd849846"
      },
      "source": [
        "!pip install pydub"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting pydub\n",
            "  Downloading pydub-0.25.1-py2.py3-none-any.whl (32 kB)\n",
            "Installing collected packages: pydub\n",
            "Successfully installed pydub-0.25.1\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SdavesC1zSrv",
        "outputId": "f18489c0-6aad-402b-bf13-d0da3b8f0617"
      },
      "source": [
        "import os\n",
        "from os import listdir\n",
        "from pathlib import Path\n",
        "\n",
        "import tensorflow as tf\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "\n",
        "import itertools\n",
        "import glob\n",
        "import random\n",
        "\n",
        "from IPython.display import Audio, Image\n",
        "from scipy.io import wavfile\n",
        "from os.path import isdir, join\n",
        "\n",
        "import librosa\n",
        "import random\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sbn\n",
        "\n",
        "from tqdm import tqdm\n",
        "\n",
        "import tensorflow_datasets as tfds\n",
        "\n",
        "from pydub import AudioSegment\n",
        "from pydub.playback import play\n",
        "import soundfile as sf\n",
        "\n",
        "import typing as T\n",
        "\n",
        "from sklearn.model_selection import StratifiedKFold\n",
        "from sklearn.model_selection import StratifiedShuffleSplit\n",
        "\n",
        "print(f\"TensorFlow Version: {tf.__version__}\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "TensorFlow Version: 2.7.0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Download the dataset"
      ],
      "metadata": {
        "id": "diuZbXxB6i0A"
      }
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sBjPSRuuzXIv",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 299,
          "referenced_widgets": [
            "0d1e0cc4415e4fcfb0c7d25e9367debd",
            "e36e782b71d1498cb496046952d4eec5",
            "403e8036e011443f9f08bcfe64618d29",
            "4273da32cd9a49b3ae700fb3d6fbedd0",
            "d8f638cdf3dd4c5497cb05a8a0fb7ad0",
            "a89873d4c2184e01adaa511d352f6bb5",
            "38a2092df6db406db8be09169b8109cd",
            "3d7d5e1359754bafaf9446af91037330",
            "7a586561029440a09a6e5ecd92228195",
            "70f789b7efc043a2bd905cd3b9edd0a7",
            "ab13cb424ba54b678428e144cac7775a",
            "42b4f020ae3049319466539b5923cffc",
            "ab6f7a1b22a3424cb2b381804bc05751",
            "115ba5781eed486799054a89c6ff95d1",
            "c537623134d94e1ea55a676ee3271f0b",
            "65d260cec9aa44029ef3b0923a2b1e39",
            "5036862f720e465a8634e2ff4f2cee9c",
            "5676bbba7e4547f9ac1cf0779ad472d2",
            "3369732b9149422d80566f4fbc8db7b0",
            "47e79578e3ec407fa7eade747fedec77",
            "082f381ba40f4762803f369f054cc987",
            "7606ff9d1fae4a1d9014b43a61004404",
            "f12b385712c3492b99ea12d9795483d2",
            "ba8e627c2a2249768b81450193bbb919",
            "72e0b17f6ca442b784bc635112a2416f",
            "82a570256dc34d76a7fbf56524d0f3d5",
            "be15ddece2584426a92ad313c5eb779a",
            "df4c61bdd443427fac6693cabc1b0e76",
            "cb77715818bd4be781aa9cafb5f7ac62",
            "1126c99c48ed4c54a42df9e62f1a8b4c",
            "b1a916d2ae1842cd9f42e37f4c4cd7c7",
            "4afdd666bcca43b0ade8d8b714686639",
            "ef6b78adc5994a9696f70a6689555268",
            "a1f6c525c69e4d9282714a6be9d048c1",
            "48fc22d8eab042f3937afd92911d3767",
            "df1fac49d5d045c09df74677a397dde2",
            "cb44cdac87d94b1eac5ec8b17a989c31",
            "3e8892ad45cc4a44b0fb527c7be56c7d",
            "650127bf9679430bbbade80ecf33d2b6",
            "b02f05313faa42569416ae4c3bdc2b00",
            "9eef7276fab14f6d95a30f96fe09f9f3",
            "87d414b67437424a88ea870a04f2c311",
            "08e2daa05c02493fb23b6f22afee9934",
            "05f1416828b8497ea9887c1bed261d20",
            "1ccbdef9fe934b5b90d193dfdce9fe33",
            "2e792dcb3b9c4b37b943f7d48bfe1f47",
            "92988901f8db4863b99a36e980246686",
            "8201474ddf17463eb39311e00d2d01c8",
            "32c9f9fdb7aa49838dd9001e7a51980b",
            "582a01c96fc7485da551d2c1fe68e72a",
            "72db5e3aaa00422e984c6c96594610aa",
            "c4eabbcc50b145679d4cf862aff34476",
            "7dce796c099543ec88b20a62a1b92ef2",
            "26baa2b121854d91a4b3d60353579ae1",
            "5701351a577d4c788a42f72d8f19b33b",
            "21ed5f6ed72146199b23c2f602ef8279",
            "7405f4b6e9a34fe38330dbc713c30ef5",
            "152c72c8d9d14f928794484d9f46ad03",
            "90de478c64894473a07531da446e3700",
            "f28ebbf31972465dabfd5f768577b2d4",
            "e0f06924177e4d2ab42dd20bc9c32148",
            "02f990ddbe864d4da39f5f8149993292",
            "8b1df2c884b44edda758a1172697601a",
            "e7ccd2b99fd340b6b1b51c688ae81728",
            "e925e9563d794cadbea985c038421f53",
            "9afc5e4fa3774f08b35cc815cc665ef7",
            "b36d78e8817645b292ff128ef86b3f5c",
            "f79d7326371248c5bb0f731e2b4f4a15",
            "87e23f3b24bf42a4b649e741752ad96c",
            "4c42c073d17840c8af1d268622f58722",
            "680ce27788ed47559ccbb74fb1b41e46",
            "7bc834feca1f45328ee5ac09fa12fe52",
            "39687c8c6e2f41fd8f072dc8822fe579",
            "adc52c96e75146ddbe9be02b137d090b",
            "77fe1cd73c924f23874607c0f6ea02b3",
            "2cf5d74e292b4b5ba44e2d64aee66276",
            "9f177d751e9f4ca5912ab376112e84af",
            "d99f40914acd40f9bbdb4c75dfd266f4",
            "288f79a7a6aa48fa9905203ccc53f0a0",
            "ea26d0c8fdc04114890f673c9d618c39",
            "926c53d1bea54f1c958eb1623de9f5eb",
            "28b7920d953841c998fc535552ebc430",
            "1763a9e63423494cb26bd7057cdd1100",
            "8502621448a74334b75c82cdf87328bb",
            "6ea7524019344be3a37a519a699589c4",
            "efccef0040b24b488993779905fa145e",
            "169d9d2cc5d148969c484fbb8d507064",
            "4208d65f74f640b1bea63f68b77d2fed"
          ]
        },
        "outputId": "b693eeac-f3e1-4df8-fc40-e93802b812ea"
      },
      "source": [
        "ds, info = tfds.load('speech_commands',\n",
        "                     split=['train', 'validation'], \n",
        "                     data_dir='dataset', \n",
        "                     with_info=True)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1mDownloading and preparing dataset speech_commands/0.0.2 (download: 2.37 GiB, generated: 8.17 GiB, total: 10.53 GiB) to dataset/speech_commands/0.0.2...\u001b[0m\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "0d1e0cc4415e4fcfb0c7d25e9367debd",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "Dl Completed...: 0 url [00:00, ? url/s]"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "42b4f020ae3049319466539b5923cffc",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "Dl Size...: 0 MiB [00:00, ? MiB/s]"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "f12b385712c3492b99ea12d9795483d2",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "0 examples [00:00, ? examples/s]"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Shuffling and writing examples to dataset/speech_commands/0.0.2.incompleteTMO8AZ/speech_commands-train.tfrecord\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "a1f6c525c69e4d9282714a6be9d048c1",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "  0%|          | 0/85511 [00:00<?, ? examples/s]"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "1ccbdef9fe934b5b90d193dfdce9fe33",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "0 examples [00:00, ? examples/s]"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Shuffling and writing examples to dataset/speech_commands/0.0.2.incompleteTMO8AZ/speech_commands-validation.tfrecord\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "21ed5f6ed72146199b23c2f602ef8279",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "  0%|          | 0/10102 [00:00<?, ? examples/s]"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "b36d78e8817645b292ff128ef86b3f5c",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "0 examples [00:00, ? examples/s]"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Shuffling and writing examples to dataset/speech_commands/0.0.2.incompleteTMO8AZ/speech_commands-test.tfrecord\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "d99f40914acd40f9bbdb4c75dfd266f4",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "  0%|          | 0/4890 [00:00<?, ? examples/s]"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1mDataset speech_commands downloaded and prepared to dataset/speech_commands/0.0.2. Subsequent calls will reuse this data.\u001b[0m\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Extract the dataset"
      ],
      "metadata": {
        "id": "EEYesmYd--KF"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!tar -xzf \"/content/dataset/downloads/down.tens.org_spee_comm_test_set_v0.2JgUkWz2DJFlHZadg2sHyT96ej1I6Owxad0OEL9yPsB8.tar.gz\" -C \"/content/dataset/downloads/extracted\"\n",
        "!tar -xzf \"/content/dataset/downloads/down.tens.org_spee_comm_test_set_v0.2JgUkWz2DJFlHZadg2sHyT96ej1I6Owxad0OEL9yPsB8.tar.gz.INFO\" -C \"/content/dataset/downloads/extracted\"\n",
        "!tar -xzf \"/content/dataset/downloads/downloa.tensorf.org_speech_command_v0.2on2wMxgCSnqce8QzXEmmpja0qys10FFJerRK-rE4AmY.tar.gz\" -C \"/content/dataset/downloads/extracted\"\n",
        "!tar -xzf \"/content/dataset/downloads/downloa.tensorf.org_speech_command_v0.2on2wMxgCSnqce8QzXEmmpja0qys10FFJerRK-rE4AmY.tar.gz.INFO\" -C \"/content/dataset/downloads/extracted\""
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PdErTK7V2RGh",
        "outputId": "645ab971-5dff-4e84-eb62-b6dceda3a161"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "gzip: stdin: not in gzip format\n",
            "tar: Child returned status 1\n",
            "tar: Error is not recoverable: exiting now\n",
            "\n",
            "gzip: stdin: not in gzip format\n",
            "tar: Child returned status 1\n",
            "tar: Error is not recoverable: exiting now\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Split the background_noise files into 1 second wav files, because they are longer than 1 second each."
      ],
      "metadata": {
        "id": "X1JGrfZth026"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "background_noise_base_dir = \"/content/dataset/downloads/extracted/_background_noise_\"\n",
        "background_noise_path = Path(background_noise_base_dir).rglob(\"*.wav\")\n",
        "\n",
        "for background_noise_audio in background_noise_path:\n",
        "  # Load the file\n",
        "\n",
        "  file_name = background_noise_audio.stem\n",
        "  audio, sr = librosa.load(background_noise_audio, sr=None)\n",
        "\n",
        "  # Split the file by second\n",
        "\n",
        "  for i in range(int(len(audio)/sr)):\n",
        "    sf.write(f\"{background_noise_base_dir}/{file_name}_{i}.wav\", audio[(i*sr):(i+1)*sr], sr)\n",
        "\n",
        "  # Remove the original file since it is not useful anymore\n",
        "\n",
        "  os.system(f\"rm {background_noise_audio}\")"
      ],
      "metadata": {
        "id": "gFO5ZDQwTblP"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Create dataset"
      ],
      "metadata": {
        "id": "be0tgsepiNNg"
      }
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SXokA_fM0A3W"
      },
      "source": [
        "dataset_path = '/content/dataset/downloads/extracted'"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6BtLTryZz-on",
        "outputId": "d1f60edf-9e01-45f7-e2f7-711df57f6e3f"
      },
      "source": [
        "# Create an all targets list\n",
        "all_targets = [name for name in listdir(dataset_path) if isdir(join(dataset_path, name))]\n",
        "\n",
        "# Sort the files because `listdir` always changes the order of listed files\n",
        "\n",
        "all_targets.sort()\n",
        "\n",
        "print(all_targets)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "['_background_noise_', '_silence_', '_unknown_', 'backward', 'bed', 'bird', 'cat', 'dog', 'down', 'eight', 'five', 'follow', 'forward', 'four', 'go', 'happy', 'house', 'learn', 'left', 'marvin', 'nine', 'no', 'off', 'on', 'one', 'right', 'seven', 'sheila', 'six', 'stop', 'three', 'tree', 'two', 'up', 'visual', 'wow', 'yes', 'zero']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lWn_ExJu1GhI"
      },
      "source": [
        "# Settings\n",
        "\n",
        "target_list = all_targets\n",
        "feature_sets_file = 'all_targets_mfcc_sets.npz'\n",
        "sample_rate = 16000 # Hz\n",
        "num_mfcc = 16\n",
        "\n",
        "# number of frames\n",
        "len_mfcc = 28"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "c7Bf1waH1AnY",
        "outputId": "2aee3a4f-e86f-4b9d-916f-cb895599c948"
      },
      "source": [
        "# Check the total number of files\n",
        "\n",
        "num_samples = 0\n",
        "for target in all_targets:\n",
        "    num_samples += len(listdir(join(dataset_path, target)))\n",
        "print('Total samples:', num_samples)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Total samples: 107044\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ohxixVvuxAIw",
        "outputId": "a072f506-8378-4400-c53a-3e033e41a829"
      },
      "source": [
        "# Create list of filenames along with ground truth vector (y)\n",
        "\n",
        "filenames = []\n",
        "y = []\n",
        "\n",
        "for index, target in enumerate(target_list):\n",
        "    print(join(dataset_path, target), \", index \", index)\n",
        "    filenames.append(listdir(join(dataset_path, target)))\n",
        "    y.append(np.ones(len(filenames[index])) * index)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/dataset/downloads/extracted/_background_noise_ , index  0\n",
            "/content/dataset/downloads/extracted/_silence_ , index  1\n",
            "/content/dataset/downloads/extracted/_unknown_ , index  2\n",
            "/content/dataset/downloads/extracted/backward , index  3\n",
            "/content/dataset/downloads/extracted/bed , index  4\n",
            "/content/dataset/downloads/extracted/bird , index  5\n",
            "/content/dataset/downloads/extracted/cat , index  6\n",
            "/content/dataset/downloads/extracted/dog , index  7\n",
            "/content/dataset/downloads/extracted/down , index  8\n",
            "/content/dataset/downloads/extracted/eight , index  9\n",
            "/content/dataset/downloads/extracted/five , index  10\n",
            "/content/dataset/downloads/extracted/follow , index  11\n",
            "/content/dataset/downloads/extracted/forward , index  12\n",
            "/content/dataset/downloads/extracted/four , index  13\n",
            "/content/dataset/downloads/extracted/go , index  14\n",
            "/content/dataset/downloads/extracted/happy , index  15\n",
            "/content/dataset/downloads/extracted/house , index  16\n",
            "/content/dataset/downloads/extracted/learn , index  17\n",
            "/content/dataset/downloads/extracted/left , index  18\n",
            "/content/dataset/downloads/extracted/marvin , index  19\n",
            "/content/dataset/downloads/extracted/nine , index  20\n",
            "/content/dataset/downloads/extracted/no , index  21\n",
            "/content/dataset/downloads/extracted/off , index  22\n",
            "/content/dataset/downloads/extracted/on , index  23\n",
            "/content/dataset/downloads/extracted/one , index  24\n",
            "/content/dataset/downloads/extracted/right , index  25\n",
            "/content/dataset/downloads/extracted/seven , index  26\n",
            "/content/dataset/downloads/extracted/sheila , index  27\n",
            "/content/dataset/downloads/extracted/six , index  28\n",
            "/content/dataset/downloads/extracted/stop , index  29\n",
            "/content/dataset/downloads/extracted/three , index  30\n",
            "/content/dataset/downloads/extracted/tree , index  31\n",
            "/content/dataset/downloads/extracted/two , index  32\n",
            "/content/dataset/downloads/extracted/up , index  33\n",
            "/content/dataset/downloads/extracted/visual , index  34\n",
            "/content/dataset/downloads/extracted/wow , index  35\n",
            "/content/dataset/downloads/extracted/yes , index  36\n",
            "/content/dataset/downloads/extracted/zero , index  37\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "skaRXYj_L03a",
        "outputId": "2dfafb60-6391-4860-8715-f9bbff6e4e7c"
      },
      "source": [
        "# Check how filenames are stored\n",
        "\n",
        "print(filenames[0:5])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[['pink_noise_38.wav', 'dude_miaowing_2.wav', 'dude_miaowing_1.wav', 'doing_the_dishes_32.wav', 'exercise_bike_6.wav', 'pink_noise_36.wav', 'doing_the_dishes_18.wav', 'doing_the_dishes_61.wav', 'running_tap_37.wav', 'white_noise_47.wav', 'running_tap_35.wav', 'pink_noise_17.wav', 'doing_the_dishes_78.wav', 'running_tap_18.wav', 'doing_the_dishes_66.wav', 'running_tap_51.wav', 'doing_the_dishes_20.wav', 'pink_noise_22.wav', 'running_tap_13.wav', 'doing_the_dishes_74.wav', 'running_tap_59.wav', 'white_noise_38.wav', 'white_noise_25.wav', 'doing_the_dishes_60.wav', 'exercise_bike_20.wav', 'white_noise_21.wav', 'pink_noise_12.wav', 'running_tap_23.wav', 'doing_the_dishes_93.wav', 'exercise_bike_3.wav', 'doing_the_dishes_82.wav', 'running_tap_36.wav', 'dude_miaowing_45.wav', 'doing_the_dishes_7.wav', 'white_noise_4.wav', 'exercise_bike_42.wav', 'dude_miaowing_58.wav', 'white_noise_24.wav', 'dude_miaowing_18.wav', 'running_tap_3.wav', 'pink_noise_6.wav', 'pink_noise_33.wav', 'pink_noise_37.wav', 'white_noise_50.wav', 'pink_noise_32.wav', 'doing_the_dishes_1.wav', 'pink_noise_35.wav', 'exercise_bike_29.wav', 'doing_the_dishes_86.wav', 'exercise_bike_18.wav', 'doing_the_dishes_58.wav', 'exercise_bike_2.wav', 'pink_noise_50.wav', 'white_noise_56.wav', 'pink_noise_26.wav', 'white_noise_2.wav', 'exercise_bike_59.wav', 'exercise_bike_32.wav', 'exercise_bike_28.wav', 'exercise_bike_49.wav', 'white_noise_27.wav', 'pink_noise_30.wav', 'white_noise_26.wav', 'doing_the_dishes_30.wav', 'running_tap_60.wav', 'dude_miaowing_30.wav', 'exercise_bike_41.wav', 'running_tap_31.wav', 'exercise_bike_12.wav', 'dude_miaowing_5.wav', 'pink_noise_55.wav', 'exercise_bike_19.wav', 'pink_noise_1.wav', 'exercise_bike_31.wav', 'running_tap_11.wav', 'exercise_bike_30.wav', 'doing_the_dishes_70.wav', 'white_noise_58.wav', 'running_tap_4.wav', 'running_tap_9.wav', 'running_tap_7.wav', 'pink_noise_47.wav', 'dude_miaowing_21.wav', 'dude_miaowing_60.wav', 'doing_the_dishes_64.wav', 'running_tap_44.wav', 'dude_miaowing_35.wav', 'dude_miaowing_27.wav', 'running_tap_47.wav', 'doing_the_dishes_38.wav', 'white_noise_13.wav', 'running_tap_22.wav', 'dude_miaowing_55.wav', 'white_noise_12.wav', 'doing_the_dishes_75.wav', 'exercise_bike_27.wav', 'running_tap_53.wav', 'white_noise_42.wav', 'doing_the_dishes_57.wav', 'dude_miaowing_6.wav', 'exercise_bike_26.wav', 'doing_the_dishes_84.wav', 'running_tap_40.wav', 'exercise_bike_14.wav', 'dude_miaowing_48.wav', 'pink_noise_46.wav', 'pink_noise_42.wav', 'white_noise_17.wav', 'pink_noise_4.wav', 'running_tap_24.wav', 'pink_noise_20.wav', 'exercise_bike_47.wav', 'running_tap_1.wav', 'white_noise_49.wav', 'pink_noise_9.wav', 'doing_the_dishes_53.wav', 'dude_miaowing_33.wav', 'white_noise_9.wav', 'doing_the_dishes_54.wav', 'running_tap_33.wav', 'doing_the_dishes_35.wav', 'exercise_bike_34.wav', 'dude_miaowing_4.wav', 'pink_noise_13.wav', 'running_tap_55.wav', 'exercise_bike_8.wav', 'dude_miaowing_47.wav', 'dude_miaowing_51.wav', 'doing_the_dishes_47.wav', 'white_noise_44.wav', 'pink_noise_44.wav', 'dude_miaowing_42.wav', 'doing_the_dishes_77.wav', 'dude_miaowing_7.wav', 'doing_the_dishes_12.wav', 'running_tap_56.wav', 'doing_the_dishes_68.wav', 'running_tap_8.wav', 'dude_miaowing_36.wav', 'doing_the_dishes_42.wav', 'dude_miaowing_0.wav', 'pink_noise_52.wav', 'white_noise_0.wav', 'pink_noise_0.wav', 'doing_the_dishes_2.wav', 'white_noise_18.wav', 'exercise_bike_33.wav', 'running_tap_14.wav', 'dude_miaowing_11.wav', 'white_noise_8.wav', 'doing_the_dishes_79.wav', 'white_noise_45.wav', 'white_noise_51.wav', 'running_tap_15.wav', 'dude_miaowing_32.wav', 'exercise_bike_57.wav', 'pink_noise_21.wav', 'pink_noise_15.wav', 'dude_miaowing_13.wav', 'white_noise_30.wav', 'white_noise_11.wav', 'exercise_bike_4.wav', 'white_noise_33.wav', 'doing_the_dishes_76.wav', 'running_tap_42.wav', 'pink_noise_28.wav', 'doing_the_dishes_34.wav', 'dude_miaowing_3.wav', 'pink_noise_14.wav', 'dude_miaowing_46.wav', 'running_tap_34.wav', 'running_tap_25.wav', 'exercise_bike_40.wav', 'running_tap_0.wav', 'white_noise_36.wav', 'doing_the_dishes_48.wav', 'running_tap_54.wav', 'running_tap_46.wav', 'pink_noise_53.wav', 'pink_noise_19.wav', 'white_noise_5.wav', 'dude_miaowing_52.wav', 'running_tap_32.wav', 'dude_miaowing_29.wav', 'doing_the_dishes_73.wav', 'pink_noise_49.wav', 'running_tap_50.wav', 'running_tap_28.wav', 'dude_miaowing_24.wav', 'white_noise_6.wav', 'pink_noise_41.wav', 'white_noise_43.wav', 'doing_the_dishes_14.wav', 'running_tap_41.wav', 'exercise_bike_7.wav', 'running_tap_20.wav', 'pink_noise_18.wav', 'exercise_bike_23.wav', 'dude_miaowing_16.wav', 'exercise_bike_10.wav', 'white_noise_39.wav', 'pink_noise_27.wav', 'exercise_bike_51.wav', 'doing_the_dishes_51.wav', 'white_noise_32.wav', 'pink_noise_58.wav', 'running_tap_12.wav', 'exercise_bike_48.wav', 'pink_noise_57.wav', 'exercise_bike_25.wav', 'dude_miaowing_53.wav', 'doing_the_dishes_46.wav', 'pink_noise_45.wav', 'doing_the_dishes_10.wav', 'dude_miaowing_38.wav', 'dude_miaowing_57.wav', 'doing_the_dishes_65.wav', 'pink_noise_5.wav', 'doing_the_dishes_25.wav', 'white_noise_31.wav', 'exercise_bike_44.wav', 'white_noise_54.wav', 'exercise_bike_5.wav', 'doing_the_dishes_56.wav', 'dude_miaowing_43.wav', 'pink_noise_16.wav', 'README.md', 'exercise_bike_17.wav', 'exercise_bike_24.wav', 'doing_the_dishes_52.wav', 'dude_miaowing_17.wav', 'doing_the_dishes_4.wav', 'pink_noise_39.wav', 'pink_noise_11.wav', 'running_tap_21.wav', 'dude_miaowing_12.wav', 'white_noise_23.wav', 'doing_the_dishes_40.wav', 'dude_miaowing_41.wav', 'dude_miaowing_28.wav', 'pink_noise_31.wav', 'doing_the_dishes_19.wav', 'doing_the_dishes_81.wav', 'running_tap_16.wav', 'dude_miaowing_10.wav', 'white_noise_20.wav', 'pink_noise_25.wav', 'running_tap_30.wav', 'doing_the_dishes_67.wav', 'doing_the_dishes_87.wav', 'exercise_bike_36.wav', 'running_tap_48.wav', 'doing_the_dishes_85.wav', 'dude_miaowing_23.wav', 'white_noise_59.wav', 'white_noise_52.wav', 'doing_the_dishes_83.wav', 'exercise_bike_21.wav', 'doing_the_dishes_28.wav', 'pink_noise_2.wav', 'exercise_bike_0.wav', 'exercise_bike_54.wav', 'doing_the_dishes_49.wav', 'doing_the_dishes_69.wav', 'exercise_bike_13.wav', 'doing_the_dishes_26.wav', 'running_tap_10.wav', 'doing_the_dishes_43.wav', 'doing_the_dishes_63.wav', 'white_noise_55.wav', 'exercise_bike_38.wav', 'doing_the_dishes_5.wav', 'running_tap_17.wav', 'dude_miaowing_8.wav', 'white_noise_37.wav', 'running_tap_26.wav', 'doing_the_dishes_36.wav', 'pink_noise_29.wav', 'dude_miaowing_50.wav', 'white_noise_14.wav', 'pink_noise_54.wav', 'doing_the_dishes_33.wav', 'exercise_bike_53.wav', 'running_tap_49.wav', 'pink_noise_43.wav', 'running_tap_45.wav', 'exercise_bike_15.wav', 'pink_noise_8.wav', 'doing_the_dishes_72.wav', 'pink_noise_10.wav', 'doing_the_dishes_24.wav', 'doing_the_dishes_6.wav', 'doing_the_dishes_11.wav', 'dude_miaowing_49.wav', 'doing_the_dishes_8.wav', 'doing_the_dishes_39.wav', 'exercise_bike_46.wav', 'white_noise_16.wav', 'exercise_bike_1.wav', 'exercise_bike_9.wav', 'doing_the_dishes_91.wav', 'white_noise_3.wav', 'running_tap_39.wav', 'doing_the_dishes_59.wav', 'doing_the_dishes_62.wav', 'white_noise_53.wav', 'doing_the_dishes_16.wav', 'dude_miaowing_34.wav', 'dude_miaowing_31.wav', 'doing_the_dishes_94.wav', 'running_tap_6.wav', 'dude_miaowing_19.wav', 'white_noise_1.wav', 'doing_the_dishes_0.wav', 'dude_miaowing_54.wav', 'pink_noise_40.wav', 'dude_miaowing_22.wav', 'doing_the_dishes_29.wav', 'exercise_bike_39.wav', 'doing_the_dishes_44.wav', 'white_noise_40.wav', 'doing_the_dishes_31.wav', 'pink_noise_59.wav', 'dude_miaowing_39.wav', 'exercise_bike_58.wav', 'doing_the_dishes_17.wav', 'exercise_bike_60.wav', 'doing_the_dishes_80.wav', 'dude_miaowing_20.wav', 'white_noise_46.wav', 'running_tap_52.wav', 'dude_miaowing_25.wav', 'doing_the_dishes_22.wav', 'running_tap_19.wav', 'doing_the_dishes_88.wav', 'white_noise_22.wav', 'exercise_bike_45.wav', 'doing_the_dishes_90.wav', 'doing_the_dishes_71.wav', 'dude_miaowing_59.wav', 'pink_noise_7.wav', 'doing_the_dishes_13.wav', 'doing_the_dishes_92.wav', 'running_tap_57.wav', 'running_tap_43.wav', 'white_noise_35.wav', 'doing_the_dishes_9.wav', 'dude_miaowing_9.wav', 'dude_miaowing_14.wav', 'dude_miaowing_37.wav', 'white_noise_41.wav', 'running_tap_58.wav', 'running_tap_38.wav', 'pink_noise_34.wav', 'exercise_bike_11.wav', 'pink_noise_3.wav', 'running_tap_29.wav', 'doing_the_dishes_37.wav', 'white_noise_15.wav', 'doing_the_dishes_23.wav', 'white_noise_34.wav', 'exercise_bike_35.wav', 'doing_the_dishes_89.wav', 'pink_noise_48.wav', 'running_tap_27.wav', 'white_noise_57.wav', 'dude_miaowing_44.wav', 'doing_the_dishes_3.wav', 'pink_noise_51.wav', 'exercise_bike_16.wav', 'pink_noise_24.wav', 'dude_miaowing_15.wav', 'white_noise_48.wav', 'exercise_bike_56.wav', 'white_noise_28.wav', 'exercise_bike_43.wav', 'white_noise_10.wav', 'doing_the_dishes_45.wav', 'white_noise_29.wav', 'doing_the_dishes_21.wav', 'exercise_bike_55.wav', 'doing_the_dishes_27.wav', 'doing_the_dishes_55.wav', 'doing_the_dishes_15.wav', 'white_noise_7.wav', 'white_noise_19.wav', 'exercise_bike_37.wav', 'doing_the_dishes_41.wav', 'dude_miaowing_26.wav', 'exercise_bike_52.wav', 'dude_miaowing_40.wav', 'running_tap_5.wav', 'doing_the_dishes_50.wav', 'dude_miaowing_56.wav', 'running_tap_2.wav', 'exercise_bike_50.wav', 'exercise_bike_22.wav', 'pink_noise_56.wav', 'pink_noise_23.wav'], ['4498.wav', '1894.wav', '1250.wav', '3542.wav', '3558.wav', '1389.wav', '835.wav', '189.wav', '325.wav', '700.wav', '1941.wav', '2682.wav', '3774.wav', '1676.wav', '4344.wav', '4860.wav', '1336.wav', '2874.wav', '861.wav', '811.wav', '4742.wav', '1929.wav', '319.wav', '92.wav', '474.wav', '2555.wav', '2870.wav', '1769.wav', '2941.wav', '1836.wav', '1421.wav', '1105.wav', '4881.wav', '1835.wav', '4767.wav', '2240.wav', '3181.wav', '1746.wav', '1749.wav', '909.wav', '781.wav', '522.wav', '3059.wav', '4609.wav', '2752.wav', '1136.wav', '2792.wav', '3025.wav', '4427.wav', '4776.wav', '1615.wav', '1342.wav', '4759.wav', '1904.wav', '1845.wav', '1115.wav', '3839.wav', '3043.wav', '3219.wav', '3131.wav', '4374.wav', '3101.wav', '4024.wav', '4848.wav', '2506.wav', '2239.wav', '3498.wav', '2203.wav', '3885.wav', '3697.wav', '1605.wav', '740.wav', '1050.wav', '4435.wav', '2467.wav', '4568.wav', '1131.wav', '4597.wav', '884.wav', '836.wav', '33.wav', '1141.wav', '2609.wav', '2750.wav', '716.wav', '4102.wav', '41.wav', '216.wav', '1024.wav', '1097.wav', '3507.wav', '4825.wav', '4173.wav', '617.wav', '1849.wav', '4383.wav', '3176.wav', '1680.wav', '3084.wav', '4431.wav', '2878.wav', '4888.wav', '2700.wav', '2935.wav', '73.wav', '1043.wav', '3967.wav', '2962.wav', '2482.wav', '4038.wav', '651.wav', '3634.wav', '4600.wav', '1420.wav', '2368.wav', '3725.wav', '127.wav', '1127.wav', '1953.wav', '2794.wav', '3434.wav', '4541.wav', '3420.wav', '2968.wav', '3228.wav', '580.wav', '1060.wav', '251.wav', '4023.wav', '2872.wav', '301.wav', '4424.wav', '158.wav', '172.wav', '2428.wav', '2641.wav', '4496.wav', '3083.wav', '4834.wav', '2980.wav', '2015.wav', '1477.wav', '3471.wav', '4042.wav', '266.wav', '3659.wav', '443.wav', '4529.wav', '1926.wav', '1708.wav', '842.wav', '252.wav', '4537.wav', '4243.wav', '4811.wav', '2744.wav', '4490.wav', '579.wav', '4149.wav', '2810.wav', '2905.wav', '2419.wav', '3956.wav', '2486.wav', '2345.wav', '1427.wav', '3231.wav', '1520.wav', '947.wav', '720.wav', '2576.wav', '4126.wav', '1766.wav', '2170.wav', '3269.wav', '1041.wav', '1357.wav', '4066.wav', '1951.wav', '3329.wav', '3622.wav', '2443.wav', '424.wav', '3826.wav', '3589.wav', '2009.wav', '2613.wav', '2193.wav', '3859.wav', '4719.wav', '1936.wav', '4157.wav', '3746.wav', '406.wav', '834.wav', '4223.wav', '3820.wav', '2942.wav', '799.wav', '2612.wav', '1295.wav', '973.wav', '3246.wav', '660.wav', '3120.wav', '924.wav', '1642.wav', '2778.wav', '2582.wav', '1292.wav', '3081.wav', '747.wav', '4123.wav', '3442.wav', '2224.wav', '1114.wav', '1561.wav', '3879.wav', '4683.wav', '1837.wav', '1685.wav', '445.wav', '4467.wav', '2320.wav', '2824.wav', '1037.wav', '3915.wav', '2583.wav', '2741.wav', '2390.wav', '3767.wav', '704.wav', '2014.wav', '4100.wav', '381.wav', '3469.wav', '4352.wav', '2388.wav', '4472.wav', '1443.wav', '2367.wav', '3535.wav', '3534.wav', '3861.wav', '282.wav', '2221.wav', '1952.wav', '788.wav', '1057.wav', '4300.wav', '4698.wav', '3123.wav', '3947.wav', '778.wav', '3831.wav', '466.wav', '561.wav', '2847.wav', '4748.wav', '1682.wav', '3333.wav', '3942.wav', '3258.wav', '2711.wav', '1181.wav', '2655.wav', '4029.wav', '2559.wav', '3347.wav', '2894.wav', '2995.wav', '1177.wav', '1540.wav', '2265.wav', '3446.wav', '4804.wav', '4214.wav', '895.wav', '1245.wav', '3211.wav', '2554.wav', '27.wav', '3519.wav', '1156.wav', '3591.wav', '93.wav', '4256.wav', '3853.wav', '3183.wav', '1922.wav', '4865.wav', '4771.wav', '2865.wav', '3391.wav', '4466.wav', '1257.wav', '926.wav', '737.wav', '3867.wav', '1366.wav', '2833.wav', '2523.wav', '3709.wav', '2846.wav', '2647.wav', '267.wav', '3513.wav', '1791.wav', '3040.wav', '463.wav', '946.wav', '3551.wav', '1816.wav', '1656.wav', '3441.wav', '2603.wav', '2689.wav', '2025.wav', '971.wav', '856.wav', '4487.wav', '4010.wav', '1516.wav', '352.wav', '727.wav', '3314.wav', '4197.wav', '3665.wav', '3911.wav', '2724.wav', '2340.wav', '4691.wav', '1649.wav', '2927.wav', '1083.wav', '4669.wav', '1287.wav', '2349.wav', '3838.wav', '35.wav', '2924.wav', '89.wav', '4815.wav', '4664.wav', '3616.wav', '3595.wav', '2575.wav', '2105.wav', '1328.wav', '58.wav', '4518.wav', '599.wav', '1428.wav', '1270.wav', '2281.wav', '3932.wav', '3373.wav', '98.wav', '3941.wav', '1254.wav', '796.wav', '2291.wav', '4.wav', '1442.wav', '2254.wav', '960.wav', '1901.wav', '2301.wav', '4583.wav', '2982.wav', '2117.wav', '3.wav', '1212.wav', '3282.wav', '623.wav', '3125.wav', '906.wav', '1370.wav', '3571.wav', '3136.wav', '4534.wav', '706.wav', '1753.wav', '3331.wav', '2262.wav', '1818.wav', '3657.wav', '4775.wav', '2197.wav', '3858.wav', '2604.wav', '1915.wav', '3474.wav', '1099.wav', '2843.wav', '4458.wav', '4196.wav', '1695.wav', '3685.wav', '1775.wav', '521.wav', '3661.wav', '2321.wav', '6.wav', '335.wav', '4072.wav', '2.wav', '167.wav'], ['forward_fb7eb481_nohash_3.wav.wav', 'eight_db24628d_nohash_2.wav.wav', 'five_964e8cfd_nohash_4.wav.wav', 'four_63f7a489_nohash_1.wav.wav', 'eight_cd85758f_nohash_0.wav.wav', 'wow_d7467392_nohash_0.wav.wav', 'one_a6f2fd71_nohash_0.wav.wav', 'seven_563aa4e6_nohash_2.wav.wav', 'three_87070229_nohash_4.wav.wav', 'wow_90b94017_nohash_0.wav.wav', 'sheila_4f8ef132_nohash_0.wav.wav', 'six_b1f8326d_nohash_0.wav.wav', 'six_f428ca69_nohash_0.wav.wav', 'six_a6f2fd71_nohash_4.wav.wav', 'cat_105a0eea_nohash_1.wav.wav', 'tree_ffb86d3c_nohash_0.wav.wav', 'nine_893705bb_nohash_0.wav.wav', 'seven_563aa4e6_nohash_1.wav.wav', 'five_fb7eb481_nohash_0.wav.wav', 'house_ca48dc76_nohash_0.wav.wav', 'bed_0ea0e2f4_nohash_1.wav.wav', 'zero_bfd26d6b_nohash_1.wav.wav', 'one_1f3bece8_nohash_1.wav.wav', 'zero_893705bb_nohash_3.wav.wav', 'one_692a88e6_nohash_1.wav.wav', 'bed_fe1916ba_nohash_0.wav.wav', 'marvin_7add4c5f_nohash_1.wav.wav', 'marvin_4f8ef132_nohash_0.wav.wav', 'happy_8494fba8_nohash_0.wav.wav', 'eight_f292725f_nohash_0.wav.wav', 'four_a591c2ea_nohash_1.wav.wav', 'nine_4f8ef132_nohash_1.wav.wav', 'eight_f292725f_nohash_1.wav.wav', 'zero_c22d3f18_nohash_2.wav.wav', 'eight_798f702a_nohash_2.wav.wav', 'three_370844f7_nohash_1.wav.wav', 'nine_d0faf7e4_nohash_2.wav.wav', 'tree_f428ca69_nohash_0.wav.wav', 'two_87070229_nohash_1.wav.wav', 'five_0cb74144_nohash_2.wav.wav', 'five_d962e5ac_nohash_0.wav.wav', 'nine_8769c34c_nohash_0.wav.wav', 'eight_cfbedff9_nohash_0.wav.wav', 'five_3b4f8f24_nohash_0.wav.wav', 'nine_fb7eb481_nohash_1.wav.wav', 'six_b97c9f77_nohash_3.wav.wav', 'bird_c7124b73_nohash_0.wav.wav', 'tree_4a0e2c16_nohash_0.wav.wav', 'visual_8769c34c_nohash_2.wav.wav', 'bird_cfde27ba_nohash_0.wav.wav', 'zero_1b4c9b89_nohash_3.wav.wav', 'forward_f2e59fea_nohash_1.wav.wav', 'five_c7124b73_nohash_0.wav.wav', 'learn_0cb74144_nohash_1.wav.wav', 'one_42beb5eb_nohash_1.wav.wav', 'forward_4c6167ca_nohash_4.wav.wav', 'follow_aa80f517_nohash_0.wav.wav', 'sheila_cfde27ba_nohash_0.wav.wav', 'nine_b1f8326d_nohash_0.wav.wav', 'six_c9b5ff26_nohash_0.wav.wav', 'dog_bed06fac_nohash_2.wav.wav', 'wow_653a48f5_nohash_0.wav.wav', 'six_d9e9f554_nohash_0.wav.wav', 'cat_83957201_nohash_0.wav.wav', 'five_798f702a_nohash_0.wav.wav', 'three_c7dc7278_nohash_1.wav.wav', 'zero_af7a8296_nohash_0.wav.wav', 'five_97f4c236_nohash_3.wav.wav', 'tree_a4e8a997_nohash_1.wav.wav', 'seven_8a325749_nohash_0.wav.wav', 'happy_4fd1443e_nohash_0.wav.wav', 'eight_7257420c_nohash_1.wav.wav', 'five_c7dc7278_nohash_0.wav.wav', 'one_837a0f64_nohash_3.wav.wav', 'marvin_3b4f8f24_nohash_0.wav.wav', 'nine_a591c2ea_nohash_3.wav.wav', 'dog_d1a4fb3f_nohash_0.wav.wav', 'zero_bfd26d6b_nohash_2.wav.wav', 'three_692a88e6_nohash_1.wav.wav', 'seven_a1533da4_nohash_0.wav.wav', 'nine_ca48dc76_nohash_0.wav.wav', 'two_aa80f517_nohash_3.wav.wav', 'seven_b83c1acf_nohash_3.wav.wav', 'backward_f9643d42_nohash_3.wav.wav', 'nine_e49428d9_nohash_0.wav.wav', 'two_964e8cfd_nohash_2.wav.wav', 'learn_1acc97de_nohash_3.wav.wav', 'marvin_f297e878_nohash_0.wav.wav', 'backward_5170b77f_nohash_4.wav.wav', 'bird_653a48f5_nohash_0.wav.wav', 'happy_8fe67225_nohash_0.wav.wav', 'zero_3b4f8f24_nohash_1.wav.wav', 'eight_c7dc7278_nohash_3.wav.wav', 'one_37dca74f_nohash_2.wav.wav', 'one_692a88e6_nohash_5.wav.wav', 'eight_893705bb_nohash_9.wav.wav', 'four_8769c34c_nohash_2.wav.wav', 'follow_bfd26d6b_nohash_4.wav.wav', 'nine_f9643d42_nohash_4.wav.wav', 'zero_db24628d_nohash_3.wav.wav', 'three_d962e5ac_nohash_0.wav.wav', 'nine_24ad3ebe_nohash_0.wav.wav', 'eight_fb7eb481_nohash_0.wav.wav', 'five_c22d3f18_nohash_4.wav.wav', 'zero_9d171fee_nohash_1.wav.wav', 'wow_6e916de8_nohash_3.wav.wav', 'learn_964c7c9e_nohash_0.wav.wav', 'three_f428ca69_nohash_0.wav.wav', 'happy_a8e25ebb_nohash_0.wav.wav', 'tree_0fa1e7a9_nohash_1.wav.wav', 'bed_837a0f64_nohash_0.wav.wav', 'three_8fe67225_nohash_3.wav.wav', 'nine_fb7eb481_nohash_0.wav.wav', 'happy_5828dfa2_nohash_1.wav.wav', 'tree_4620dc14_nohash_0.wav.wav', 'four_4c6167ca_nohash_4.wav.wav', 'bird_0fa1e7a9_nohash_0.wav.wav', 'eight_82b99576_nohash_0.wav.wav', 'zero_af8b2f2c_nohash_0.wav.wav', 'seven_91b03183_nohash_3.wav.wav', 'three_e41a903b_nohash_0.wav.wav', 'eight_f9643d42_nohash_2.wav.wav', 'sheila_44260689_nohash_0.wav.wav', 'eight_2d82a556_nohash_1.wav.wav', 'two_e49428d9_nohash_1.wav.wav', 'eight_9d4bab4f_nohash_1.wav.wav', 'two_e49428d9_nohash_0.wav.wav', 'house_84d1e469_nohash_0.wav.wav', 'nine_1b4c9b89_nohash_2.wav.wav', 'zero_837a0f64_nohash_3.wav.wav', 'house_7e1054e7_nohash_1.wav.wav', 'cat_2d82a556_nohash_0.wav.wav', 'marvin_0c40e715_nohash_0.wav.wav', 'dog_4c6167ca_nohash_1.wav.wav', 'six_1acc97de_nohash_2.wav.wav', 'backward_f2e59fea_nohash_4.wav.wav', 'marvin_af130f12_nohash_0.wav.wav', 'six_3659fc1c_nohash_0.wav.wav', 'eight_7257420c_nohash_0.wav.wav', 'follow_b7e9f841_nohash_0.wav.wav', 'sheila_4c6167ca_nohash_1.wav.wav', 'nine_3df9a3d4_nohash_0.wav.wav', 'cat_7192fddc_nohash_0.wav.wav', 'cat_4620dc14_nohash_0.wav.wav', 'forward_a7216980_nohash_2.wav.wav', 'six_5c8af87a_nohash_0.wav.wav', 'eight_4fd1443e_nohash_2.wav.wav', 'bird_e71b4ce6_nohash_0.wav.wav', 'bed_4c7c95de_nohash_0.wav.wav', 'six_692a88e6_nohash_0.wav.wav', 'sheila_af405b69_nohash_1.wav.wav', 'one_8769c34c_nohash_0.wav.wav', 'forward_d5b963aa_nohash_3.wav.wav', 'eight_f2e59fea_nohash_2.wav.wav', 'forward_3b4f8f24_nohash_2.wav.wav', 'wow_a4383927_nohash_0.wav.wav', 'tree_8ea6dec6_nohash_0.wav.wav', 'three_8c0e5970_nohash_0.wav.wav', 'happy_e0c782d5_nohash_0.wav.wav', 'four_c9b5ff26_nohash_3.wav.wav', 'nine_964e8cfd_nohash_1.wav.wav', 'eight_80c45ed6_nohash_1.wav.wav', 'eight_97f4c236_nohash_1.wav.wav', 'bird_a4383927_nohash_0.wav.wav', 'three_87070229_nohash_1.wav.wav', 'one_4845bb10_nohash_0.wav.wav', 'eight_bb05582b_nohash_3.wav.wav', 'six_27c30960_nohash_1.wav.wav', 'forward_cfbedff9_nohash_0.wav.wav', 'eight_18f8afd5_nohash_3.wav.wav', 'wow_3b4f8f24_nohash_0.wav.wav', 'wow_dc75148d_nohash_0.wav.wav', 'one_0cb74144_nohash_1.wav.wav', 'three_9a69672b_nohash_1.wav.wav', 'one_8fe52b97_nohash_0.wav.wav', 'nine_563aa4e6_nohash_4.wav.wav', 'four_b49caed3_nohash_0.wav.wav', 'bird_5c8af87a_nohash_0.wav.wav', 'house_b11a05d2_nohash_0.wav.wav', 'forward_4fd1443e_nohash_1.wav.wav', 'five_0d53e045_nohash_0.wav.wav', 'four_8ec6dab6_nohash_1.wav.wav', 'three_27c30960_nohash_0.wav.wav', 'two_5e3dde6b_nohash_1.wav.wav', 'two_4fd1443e_nohash_3.wav.wav', 'two_4fd1443e_nohash_1.wav.wav', 'eight_c0e0f834_nohash_0.wav.wav', 'two_18f8afd5_nohash_2.wav.wav', 'happy_d91a159e_nohash_0.wav.wav', 'four_cfbedff9_nohash_0.wav.wav', 'eight_837a0f64_nohash_4.wav.wav', 'happy_3df9a3d4_nohash_0.wav.wav', 'house_6e916de8_nohash_0.wav.wav', 'five_837a0f64_nohash_4.wav.wav', 'wow_4f8ef132_nohash_0.wav.wav', 'three_4c7c95de_nohash_0.wav.wav', 'zero_d962e5ac_nohash_4.wav.wav', 'six_63f7a489_nohash_0.wav.wav', 'six_9dc1889e_nohash_1.wav.wav', 'happy_893705bb_nohash_1.wav.wav', 'zero_5e3dde6b_nohash_2.wav.wav', 'five_893705bb_nohash_8.wav.wav', 'five_9d4bab4f_nohash_1.wav.wav', 'nine_26b28ea7_nohash_0.wav.wav', 'one_2796ac50_nohash_0.wav.wav', 'four_a8e25ebb_nohash_2.wav.wav', 'tree_0c40e715_nohash_2.wav.wav', 'forward_893705bb_nohash_4.wav.wav', 'six_9a69672b_nohash_1.wav.wav', 'six_43fc47a7_nohash_0.wav.wav', 'one_27c30960_nohash_1.wav.wav', 'one_d962e5ac_nohash_3.wav.wav', 'one_cfbedff9_nohash_0.wav.wav', 'six_db24628d_nohash_0.wav.wav', 'tree_7add4c5f_nohash_0.wav.wav', 'two_91b03183_nohash_1.wav.wav', 'six_0cb74144_nohash_1.wav.wav', 'wow_a591c2ea_nohash_0.wav.wav', 'forward_8fe67225_nohash_3.wav.wav', 'zero_0fa1e7a9_nohash_2.wav.wav', 'zero_563aa4e6_nohash_2.wav.wav', 'wow_aa80f517_nohash_0.wav.wav', 'happy_7bae88ed_nohash_0.wav.wav', 'bird_2c6d3924_nohash_0.wav.wav', 'backward_a6f2fd71_nohash_3.wav.wav', 'sheila_af130f12_nohash_3.wav.wav', 'five_a80f9f53_nohash_0.wav.wav', 'bird_d5b963aa_nohash_0.wav.wav', 'eight_0c40e715_nohash_0.wav.wav', 'follow_4c6167ca_nohash_3.wav.wav', 'eight_964e8cfd_nohash_2.wav.wav', 'visual_ea37ca08_nohash_0.wav.wav', 'one_9a69672b_nohash_0.wav.wav', 'two_8769c34c_nohash_4.wav.wav', 'nine_4fd1443e_nohash_0.wav.wav', 'one_d5ca80c6_nohash_0.wav.wav', 'two_0ea0e2f4_nohash_2.wav.wav', 'two_893705bb_nohash_0.wav.wav', 'eight_893705bb_nohash_0.wav.wav', 'sheila_6021f08b_nohash_0.wav.wav', 'visual_8769c34c_nohash_0.wav.wav', 'five_4fd1443e_nohash_1.wav.wav', 'happy_6b889021_nohash_2.wav.wav', 'two_a4e8a997_nohash_0.wav.wav', 'one_4fd1443e_nohash_2.wav.wav', 'marvin_b2e2773a_nohash_0.wav.wav', 'one_dfdabe19_nohash_1.wav.wav', 'eight_e49428d9_nohash_1.wav.wav', 'house_412c675c_nohash_0.wav.wav', 'happy_1f653d27_nohash_1.wav.wav', 'bed_bed06fac_nohash_0.wav.wav', 'happy_f6af2457_nohash_0.wav.wav', 'sheila_8fe52b97_nohash_0.wav.wav', 'zero_44260689_nohash_0.wav.wav', 'zero_81dc4a94_nohash_1.wav.wav', 'four_db24628d_nohash_1.wav.wav', 'happy_24ad3ebe_nohash_0.wav.wav', 'zero_5170b77f_nohash_1.wav.wav', 'seven_e49428d9_nohash_3.wav.wav', 'six_a80f9f53_nohash_0.wav.wav', 'three_b1f8326d_nohash_0.wav.wav', 'happy_a7216980_nohash_0.wav.wav', 'follow_b7e9f841_nohash_2.wav.wav', 'learn_0cb74144_nohash_0.wav.wav', 'six_b49caed3_nohash_0.wav.wav', 'visual_ca4d5368_nohash_5.wav.wav', 'three_a80f9f53_nohash_0.wav.wav', 'zero_44260689_nohash_1.wav.wav', 'house_8c7f81df_nohash_1.wav.wav', 'four_5170b77f_nohash_2.wav.wav', 'backward_8fe67225_nohash_4.wav.wav', 'happy_b1f8326d_nohash_1.wav.wav', 'six_8fe67225_nohash_4.wav.wav', 'zero_5170b77f_nohash_4.wav.wav', 'two_8769c34c_nohash_1.wav.wav', 'sheila_5b1db3ee_nohash_1.wav.wav', 'nine_964e8cfd_nohash_2.wav.wav', 'seven_cd85758f_nohash_0.wav.wav', 'four_bfd26d6b_nohash_1.wav.wav', 'cat_105a0eea_nohash_0.wav.wav', 'bed_5e3dde6b_nohash_0.wav.wav', 'four_18f8afd5_nohash_0.wav.wav', 'three_6736bc64_nohash_2.wav.wav', 'two_e1469561_nohash_3.wav.wav', 'seven_9d4bab4f_nohash_0.wav.wav', 'learn_ca4d5368_nohash_0.wav.wav', 'five_42beb5eb_nohash_0.wav.wav', 'three_b97c9f77_nohash_4.wav.wav', 'eight_67961766_nohash_0.wav.wav', 'six_a7216980_nohash_3.wav.wav', 'cat_8fe67225_nohash_0.wav.wav', 'seven_d1bf406b_nohash_1.wav.wav', 'six_964e8cfd_nohash_2.wav.wav', 'marvin_105a0eea_nohash_0.wav.wav', 'sheila_ca48dc76_nohash_1.wav.wav', 'six_dfdabe19_nohash_0.wav.wav', 'five_2aa787cf_nohash_1.wav.wav', 'dog_85d2ac4b_nohash_2.wav.wav', 'four_bfd26d6b_nohash_0.wav.wav', 'four_caedb73a_nohash_1.wav.wav', 'five_a6f2fd71_nohash_0.wav.wav', 'one_3b4f8f24_nohash_0.wav.wav', 'one_d5b963aa_nohash_0.wav.wav', 'three_fa446c16_nohash_0.wav.wav', 'sheila_4c841771_nohash_1.wav.wav', 'follow_e49428d9_nohash_2.wav.wav', 'seven_cd85758f_nohash_3.wav.wav', 'eight_b83c1acf_nohash_0.wav.wav', 'house_2aa787cf_nohash_1.wav.wav', 'tree_aef8dcf5_nohash_0.wav.wav', 'dog_2c6d3924_nohash_2.wav.wav', 'zero_c7dc7278_nohash_1.wav.wav', 'three_91b03183_nohash_3.wav.wav', 'nine_b1f8326d_nohash_1.wav.wav', 'one_82d0d3ba_nohash_0.wav.wav', 'bed_893705bb_nohash_2.wav.wav', 'one_b97c9f77_nohash_3.wav.wav', 'one_d0faf7e4_nohash_1.wav.wav', 'marvin_587f3271_nohash_0.wav.wav', 'learn_1acc97de_nohash_0.wav.wav', 'four_d1bf406b_nohash_0.wav.wav', 'dog_43fc47a7_nohash_0.wav.wav', 'seven_e0c782d5_nohash_2.wav.wav', 'eight_a7216980_nohash_1.wav.wav', 'learn_475b61f1_nohash_0.wav.wav', 'zero_bb05582b_nohash_0.wav.wav', 'happy_37fc5d97_nohash_1.wav.wav', 'eight_97f4c236_nohash_3.wav.wav', 'learn_e49428d9_nohash_4.wav.wav', 'eight_fe1916ba_nohash_0.wav.wav', 'learn_b7e9f841_nohash_0.wav.wav', 'four_0c40e715_nohash_0.wav.wav', 'eight_94de6a6a_nohash_3.wav.wav', 'three_7192fddc_nohash_0.wav.wav', 'happy_1fe4c891_nohash_1.wav.wav', 'two_e0c782d5_nohash_1.wav.wav', 'seven_5f814c23_nohash_0.wav.wav', 'backward_bfd26d6b_nohash_2.wav.wav', 'wow_af405b69_nohash_0.wav.wav', 'wow_5744b6a7_nohash_1.wav.wav', 'six_1acc97de_nohash_0.wav.wav', 'two_84d1e469_nohash_0.wav.wav', 'follow_63f7a489_nohash_1.wav.wav', 'cat_c518d1b1_nohash_0.wav.wav', 'zero_d0faf7e4_nohash_4.wav.wav', 'two_fce96bac_nohash_1.wav.wav', 'forward_c7dc7278_nohash_2.wav.wav', 'forward_4c6167ca_nohash_5.wav.wav', 'seven_fb7eb481_nohash_1.wav.wav', 'three_ca4d5368_nohash_2.wav.wav', 'three_ef2a3cfb_nohash_0.wav.wav', 'happy_d1a4fb3f_nohash_0.wav.wav', 'bed_ca4d5368_nohash_0.wav.wav', 'seven_bfd26d6b_nohash_1.wav.wav', 'five_4c841771_nohash_0.wav.wav', 'sheila_881583a6_nohash_0.wav.wav', 'wow_4290ca61_nohash_1.wav.wav', 'sheila_370844f7_nohash_0.wav.wav', 'five_7dc95912_nohash_1.wav.wav', 'six_3efef882_nohash_0.wav.wav', 'marvin_6379c6a2_nohash_0.wav.wav', 'five_c9b5ff26_nohash_1.wav.wav', 'backward_0c540988_nohash_0.wav.wav', 'nine_b97c9f77_nohash_0.wav.wav', 'wow_81dc4a94_nohash_0.wav.wav', 'six_d5b963aa_nohash_3.wav.wav', 'dog_b97c9f77_nohash_0.wav.wav', 'happy_f17d21b5_nohash_0.wav.wav', 'follow_893705bb_nohash_9.wav.wav', 'marvin_d1bf406b_nohash_0.wav.wav', 'two_d5ca80c6_nohash_3.wav.wav', 'six_653a48f5_nohash_0.wav.wav', 'backward_87070229_nohash_2.wav.wav', 'three_692a88e6_nohash_3.wav.wav', 'seven_9b3ea809_nohash_0.wav.wav', 'zero_cfbedff9_nohash_0.wav.wav', 'cat_6f2f57c1_nohash_0.wav.wav', 'wow_a2473d62_nohash_1.wav.wav', 'four_c7dc7278_nohash_0.wav.wav', 'nine_7257420c_nohash_0.wav.wav', 'backward_0cb74144_nohash_2.wav.wav', 'six_4c6167ca_nohash_5.wav.wav', 'bird_b97c9f77_nohash_0.wav.wav', 'learn_220ee1ef_nohash_0.wav.wav', 'sheila_bed06fac_nohash_0.wav.wav', 'nine_6b889021_nohash_0.wav.wav', 'sheila_283d7a53_nohash_0.wav.wav', 'nine_af405b69_nohash_0.wav.wav', 'three_c9b5ff26_nohash_0.wav.wav', 'sheila_a1533da4_nohash_1.wav.wav', 'visual_e49428d9_nohash_4.wav.wav', 'five_aa80f517_nohash_1.wav.wav', 'bed_cfbedff9_nohash_0.wav.wav', 'three_fb7eb481_nohash_2.wav.wav', 'house_cd85758f_nohash_0.wav.wav', 'visual_91b03183_nohash_4.wav.wav', 'eight_8a325749_nohash_1.wav.wav', 'sheila_d9e9f554_nohash_0.wav.wav', 'seven_7e1054e7_nohash_0.wav.wav', 'seven_964e8cfd_nohash_1.wav.wav', 'one_7257420c_nohash_0.wav.wav', 'follow_e0c782d5_nohash_0.wav.wav', 'forward_f9643d42_nohash_2.wav.wav', 'three_e9901cf0_nohash_1.wav.wav', 'cat_d5ca80c6_nohash_0.wav.wav', 'bed_28497c5b_nohash_0.wav.wav', 'happy_e49428d9_nohash_0.wav.wav', 'house_e1469561_nohash_0.wav.wav'], ['cc8b3228_nohash_2.wav', '513aeddf_nohash_2.wav', '4e6902d0_nohash_1.wav', 'f2e9b610_nohash_0.wav', '7e7ca854_nohash_2.wav', 'ace82a68_nohash_0.wav', 'aa80f517_nohash_1.wav', '3f45a0cf_nohash_1.wav', 'f798ac78_nohash_4.wav', '6ef407da_nohash_0.wav', '9f93e408_nohash_0.wav', '4e6902d0_nohash_0.wav', 'beb458a4_nohash_4.wav', 'ca4d5368_nohash_2.wav', '821b64cc_nohash_4.wav', 'a7acbbeb_nohash_0.wav', '62f05757_nohash_4.wav', '1b18600d_nohash_0.wav', '617aeb6c_nohash_4.wav', 'a6f2fd71_nohash_4.wav', '18f8afd5_nohash_1.wav', 'aa80f517_nohash_3.wav', '7fb8d703_nohash_2.wav', '42a99aec_nohash_2.wav', '9448c397_nohash_2.wav', '2aca1e72_nohash_3.wav', '32ad5b65_nohash_2.wav', '6fb3d5a7_nohash_3.wav', 'bfd26d6b_nohash_3.wav', 'fbb56351_nohash_1.wav', '0d6d7360_nohash_2.wav', 'ef3367d9_nohash_4.wav', '7c86c03e_nohash_0.wav', '8fe67225_nohash_2.wav', '52162b51_nohash_0.wav', '6565a81d_nohash_0.wav', 'f0659908_nohash_1.wav', 'ee1d8d49_nohash_0.wav', '7e7ca854_nohash_4.wav', '050170cb_nohash_4.wav', '6124b431_nohash_3.wav', '0d82fd99_nohash_2.wav', 'ddedba85_nohash_1.wav', '3b195250_nohash_2.wav', '0f46028a_nohash_4.wav', 'eaa83485_nohash_2.wav', '6aa8def4_nohash_1.wav', '85851131_nohash_2.wav', '64df20d8_nohash_2.wav', 'be0f2293_nohash_0.wav', 'bdd22e4d_nohash_0.wav', 'fa57ab3b_nohash_1.wav', '226537ab_nohash_0.wav', 'a16013b7_nohash_1.wav', 'f035e2ea_nohash_5.wav', 'ab9b93e4_nohash_2.wav', '8dc18a75_nohash_0.wav', 'd962e5ac_nohash_2.wav', '845f8553_nohash_0.wav', '6379c6a2_nohash_0.wav', 'f822b9bf_nohash_3.wav', 'eeaf97c3_nohash_2.wav', 'c50f55b8_nohash_9.wav', 'b2ae3928_nohash_1.wav', '25e95412_nohash_2.wav', 'ceef6d96_nohash_0.wav', 'c9b5ff26_nohash_2.wav', '608473c9_nohash_0.wav', '98ea0818_nohash_5.wav', '5cf1ecce_nohash_3.wav', 'cfbedff9_nohash_0.wav', '211b928a_nohash_0.wav', 'f0522ff4_nohash_4.wav', 'f30285c8_nohash_0.wav', 'd962e5ac_nohash_4.wav', 'b2ae3928_nohash_0.wav', '54ad8f22_nohash_2.wav', '91b03183_nohash_2.wav', 'e11fbc6e_nohash_0.wav', '6fb3d5a7_nohash_4.wav', 'b5cf6ea8_nohash_4.wav', '9fa86a74_nohash_0.wav', 'b29f8b23_nohash_1.wav', 'bbf38549_nohash_3.wav', '7fb8d703_nohash_1.wav', 'ee1d8d49_nohash_2.wav', '676f8138_nohash_1.wav', 'da040491_nohash_2.wav', 'a6f2fd71_nohash_1.wav', 'f2898d06_nohash_0.wav', '1b18600d_nohash_1.wav', '234d6a48_nohash_2.wav', 'dd664d92_nohash_0.wav', '9be15e93_nohash_3.wav', 'acfd5b5e_nohash_3.wav', '460209ac_nohash_1.wav', 'ab46af55_nohash_0.wav', 'ef77b778_nohash_4.wav', 'c351e611_nohash_4.wav', '0a396ff2_nohash_0.wav', 'ef3367d9_nohash_1.wav', '69a1a79f_nohash_3.wav', 'f1d8a638_nohash_1.wav', '5170b77f_nohash_1.wav', '0d90d8e1_nohash_0.wav', 'ff2b842e_nohash_1.wav', '0a2b400e_nohash_4.wav', 'b8874962_nohash_1.wav', '88e730cd_nohash_1.wav', 'ff4ed4f3_nohash_3.wav', '821b64cc_nohash_0.wav', 'e11fbc6e_nohash_3.wav', 'e882abb2_nohash_1.wav', '833d9f56_nohash_1.wav', '6fb3d5a7_nohash_0.wav', '983577be_nohash_0.wav', 'ef3367d9_nohash_2.wav', 'e882abb2_nohash_0.wav', '4340d369_nohash_0.wav', '131e738d_nohash_0.wav', 'cc3b5b62_nohash_3.wav', '3108acca_nohash_1.wav', '63ae15e4_nohash_0.wav', '3e6e5b0f_nohash_0.wav', '460209ac_nohash_2.wav', 'a04817c2_nohash_4.wav', 'e4be0cf6_nohash_2.wav', '779de043_nohash_3.wav', 'a16013b7_nohash_3.wav', '72242187_nohash_0.wav', 'fb8c31a9_nohash_3.wav', 'ebdd0f59_nohash_1.wav', '525eaa62_nohash_0.wav', '7d6b4b10_nohash_4.wav', '7f9eb952_nohash_0.wav', '113b3fbc_nohash_3.wav', '4fd1443e_nohash_1.wav', '02ade946_nohash_1.wav', 'd962e5ac_nohash_0.wav', '833d9f56_nohash_0.wav', '51c5601d_nohash_1.wav', 'fd9c7413_nohash_0.wav', '98ea0818_nohash_2.wav', 'f822b9bf_nohash_1.wav', '1f3e4139_nohash_0.wav', '017c4098_nohash_1.wav', '5a5721f8_nohash_2.wav', '234d6a48_nohash_0.wav', '113b3fbc_nohash_0.wav', '189cbabe_nohash_0.wav', '2927c601_nohash_1.wav', 'c7dc7278_nohash_2.wav', '1b627376_nohash_0.wav', 'fd5ccd39_nohash_0.wav', 'ef3367d9_nohash_7.wav', '4e6902d0_nohash_3.wav', '9151f184_nohash_2.wav', '9fac5701_nohash_2.wav', 'ace82a68_nohash_1.wav', '1dc86f91_nohash_0.wav', '64df20d8_nohash_0.wav', '067f61e2_nohash_3.wav', 'bcf614a2_nohash_4.wav', '3d794813_nohash_0.wav', 'b308773d_nohash_1.wav', '8fe67225_nohash_1.wav', '3a69f765_nohash_2.wav', '578d3efb_nohash_3.wav', '7c83c5f6_nohash_3.wav', '90e72357_nohash_1.wav', '8b25410a_nohash_3.wav', 'ec989d6d_nohash_1.wav', '4f558007_nohash_0.wav', '70880cc6_nohash_1.wav', '87d5e978_nohash_2.wav', 'ff2b842e_nohash_2.wav', '890cc926_nohash_3.wav', '1acc97de_nohash_3.wav', '8e080ece_nohash_0.wav', 'bcf614a2_nohash_3.wav', '3c4aa5ef_nohash_0.wav', 'fb7eb481_nohash_4.wav', 'a7acbbeb_nohash_1.wav', '1ed0b13d_nohash_2.wav', 'e71a9381_nohash_3.wav', '96d8bb6f_nohash_1.wav', '9a76f8c3_nohash_0.wav', '833d9f56_nohash_3.wav', 'd4dddb92_nohash_1.wav', 'c0cb43d6_nohash_0.wav', '9b8a7439_nohash_0.wav', '8dc18a75_nohash_1.wav', '333d7ddb_nohash_3.wav', '5f5eef60_nohash_2.wav', 'd21fd169_nohash_1.wav', '3a3ee7ed_nohash_3.wav', '472b8045_nohash_0.wav', '7c83c5f6_nohash_4.wav', 'bde0f20a_nohash_0.wav', '7fb8d703_nohash_3.wav', 'b8874962_nohash_0.wav', '1c84a139_nohash_4.wav', '878befa7_nohash_2.wav', '0585b66d_nohash_0.wav', '9b8a7439_nohash_2.wav', '95fd5a0f_nohash_1.wav', 'bb6d4301_nohash_1.wav', 'bbf38549_nohash_2.wav', '3589bc72_nohash_2.wav', 'a04817c2_nohash_0.wav', 'b528edb3_nohash_4.wav', '0ea9c8ce_nohash_4.wav', '18e910f4_nohash_3.wav', 'dae01802_nohash_0.wav', '645ed69d_nohash_0.wav', 'ea0cf37f_nohash_0.wav', 'c41d9052_nohash_0.wav', 'b5eb4f9b_nohash_0.wav', '54ad8f22_nohash_0.wav', '19a1e5c7_nohash_0.wav', '3b195250_nohash_1.wav', 'cb72dfb6_nohash_0.wav', 'b5cf6ea8_nohash_3.wav', '8e523821_nohash_1.wav', 'b76f6088_nohash_0.wav', '472b8045_nohash_2.wav', '211b928a_nohash_1.wav', '1acc97de_nohash_2.wav', '42a99aec_nohash_3.wav', '2aca1e72_nohash_5.wav', 'b91b718c_nohash_3.wav', '61e2f74f_nohash_0.wav', 'ec9b830b_nohash_0.wav', 'c98bbbd3_nohash_2.wav', '235b444f_nohash_0.wav', '81332c92_nohash_2.wav', '2aca1e72_nohash_1.wav', '88d009d2_nohash_0.wav', '8b367d88_nohash_0.wav', '728be664_nohash_1.wav', 'd1dd03ed_nohash_1.wav', '91ffb786_nohash_0.wav', 'e71a9381_nohash_0.wav', 'bb05582b_nohash_2.wav', '2005ca25_nohash_0.wav', 'a9ca1818_nohash_1.wav', 'eaa83485_nohash_0.wav', 'fb7eb481_nohash_0.wav', 'a928cc5b_nohash_0.wav', '2927c601_nohash_3.wav', 'ec989d6d_nohash_0.wav', 'ca4912b6_nohash_1.wav', 'b91b718c_nohash_2.wav', '85c60942_nohash_0.wav', 'dae01802_nohash_1.wav', '0a2b400e_nohash_2.wav', '6124b431_nohash_1.wav', 'd4dddb92_nohash_3.wav', '9b8a7439_nohash_1.wav', '256c0a05_nohash_4.wav', 'f2f0d244_nohash_0.wav', 'c50f55b8_nohash_19.wav', '57152045_nohash_4.wav', 'd3831f6a_nohash_2.wav', '51f7a034_nohash_4.wav', '0cb74144_nohash_3.wav', 'de3fe344_nohash_0.wav', 'a1cf7fd8_nohash_1.wav', '4fd1443e_nohash_2.wav', '0e6e36c9_nohash_4.wav', '6969e51a_nohash_1.wav', 'ed032775_nohash_1.wav', '5a5721f8_nohash_1.wav', 'b5cf6ea8_nohash_7.wav', 'aa80f517_nohash_0.wav', 'f0659908_nohash_4.wav', '7a49163e_nohash_1.wav', '9b02d503_nohash_2.wav', '7ce8df21_nohash_0.wav', 'de89e2ca_nohash_2.wav', '6124b431_nohash_0.wav', '1e9e6bdd_nohash_0.wav', '1589451d_nohash_0.wav', 'a1cf7fd8_nohash_0.wav', 'b6573c88_nohash_0.wav', 'ab46af55_nohash_2.wav', 'd1dd03ed_nohash_3.wav', '03401e93_nohash_1.wav', '837a0f64_nohash_0.wav', 'c98bbbd3_nohash_1.wav', 'b4ea0d9a_nohash_0.wav', 'fd5ccd39_nohash_4.wav', '74241b28_nohash_4.wav', '32ad5b65_nohash_1.wav', '508e30ee_nohash_0.wav', 'da93deb7_nohash_0.wav', 'f2e9b610_nohash_3.wav', '1c84a139_nohash_1.wav', 'ca4912b6_nohash_3.wav', '195c120a_nohash_1.wav', 'a929f9b9_nohash_1.wav', 'd394ef8e_nohash_3.wav', '234d6a48_nohash_1.wav', 'ec989d6d_nohash_4.wav', 'c7dc7278_nohash_0.wav', 'fc3ba625_nohash_2.wav', 'cb72dfb6_nohash_3.wav', '4cee0c60_nohash_0.wav', 'a7216980_nohash_0.wav', '5f5eef60_nohash_0.wav', 'cc3b5b62_nohash_2.wav', '63f7a489_nohash_0.wav', '24a3e589_nohash_2.wav', 'f2e59fea_nohash_3.wav', '3102f006_nohash_0.wav', 'c2dccf38_nohash_2.wav', '8e523821_nohash_0.wav', '1ed0b13d_nohash_3.wav', '833d9f56_nohash_2.wav', '72e382bd_nohash_0.wav', 'dae01802_nohash_2.wav', '31f01a8d_nohash_0.wav', '017c4098_nohash_0.wav', 'e4be0cf6_nohash_3.wav', '5769c5ab_nohash_4.wav', '9f93e408_nohash_1.wav', '3d794813_nohash_1.wav', 'c50f55b8_nohash_8.wav', 'd264f7b6_nohash_0.wav', 'b69fe0e2_nohash_3.wav', '61ab8fbc_nohash_1.wav', 'e3e0f145_nohash_3.wav', '773e26f7_nohash_2.wav', '1a994c9f_nohash_4.wav', '8f447c3e_nohash_1.wav', '51f7a034_nohash_3.wav', '4c6944d6_nohash_5.wav', 'ceef6d96_nohash_2.wav', '0ba018fc_nohash_3.wav', '617aeb6c_nohash_0.wav', '42f81601_nohash_0.wav', '3cc595de_nohash_2.wav', '9be15e93_nohash_1.wav', '460209ac_nohash_3.wav', '773e26f7_nohash_4.wav', '2a1f4853_nohash_2.wav', '472b8045_nohash_1.wav', 'ab46af55_nohash_1.wav', '1b42b551_nohash_1.wav', 'b0f5b16d_nohash_4.wav', 'bde0f20a_nohash_3.wav', 'e49428d9_nohash_0.wav', '0b7ee1a0_nohash_4.wav', '235b444f_nohash_2.wav', '1b42b551_nohash_3.wav', 'a1e71565_nohash_3.wav', '90e72357_nohash_0.wav', '86f3558f_nohash_0.wav', '72242187_nohash_4.wav', '7622d95b_nohash_2.wav', 'd3831f6a_nohash_1.wav', '94d370bf_nohash_2.wav', '2927c601_nohash_0.wav', '0ea9c8ce_nohash_1.wav', 'a7200079_nohash_1.wav', '55feffd5_nohash_0.wav', 'ef3367d9_nohash_0.wav', '1acc97de_nohash_0.wav', '6969e51a_nohash_2.wav', '1dc86f91_nohash_2.wav', '42f81601_nohash_2.wav', '57152045_nohash_2.wav', '1e02ffc5_nohash_3.wav', '0d82fd99_nohash_3.wav', '0f46028a_nohash_3.wav', '256c0a05_nohash_3.wav', '616420be_nohash_2.wav', '7a49163e_nohash_0.wav', '3cc595de_nohash_0.wav', 'a045368c_nohash_1.wav', '95fd5a0f_nohash_0.wav', 'cc4f9250_nohash_4.wav', '0ba018fc_nohash_1.wav', '1b42b551_nohash_4.wav', 'b44007bc_nohash_1.wav', '113b3fbc_nohash_1.wav', '54aecbd5_nohash_0.wav', 'e9bc5cc2_nohash_2.wav', 'c50f55b8_nohash_6.wav', '72e382bd_nohash_4.wav', '256c0a05_nohash_0.wav', '0a2b400e_nohash_1.wav', 'cc8b3228_nohash_1.wav', 'a929f9b9_nohash_4.wav', 'd4dddb92_nohash_2.wav', '368bedd4_nohash_0.wav', 'e6327279_nohash_2.wav', 'f9643d42_nohash_3.wav', 'ae32324a_nohash_0.wav', '64e48f55_nohash_1.wav', '1496195a_nohash_2.wav', '1ed0b13d_nohash_1.wav', '645ed69d_nohash_4.wav', '9fac5701_nohash_3.wav', 'cc3b5b62_nohash_1.wav', '0d90d8e1_nohash_3.wav', 'ff4ed4f3_nohash_2.wav', 'd1526c4e_nohash_1.wav', 'b414c653_nohash_0.wav', '0f7266cf_nohash_1.wav', '0b7ee1a0_nohash_1.wav', '3bb68054_nohash_3.wav', 'bb6d4301_nohash_3.wav', '74241b28_nohash_1.wav', '62ccd358_nohash_0.wav', '8d5e1dc0_nohash_0.wav', '9fac5701_nohash_1.wav', '42398aab_nohash_1.wav', '833d9f56_nohash_4.wav', '0d90d8e1_nohash_1.wav', 'f736ab63_nohash_3.wav', 'b308773d_nohash_2.wav', '7c83c5f6_nohash_0.wav', '679463fc_nohash_1.wav', '6bf5baf3_nohash_2.wav', 'a9ca1818_nohash_0.wav', 'a489191a_nohash_1.wav', '893705bb_nohash_8.wav', '87070229_nohash_3.wav', 'd9aa8c90_nohash_0.wav', 'acb9db68_nohash_1.wav', 'd264f7b6_nohash_2.wav', '3bb68054_nohash_1.wav', '244cc3a5_nohash_0.wav', 'a55105d0_nohash_3.wav', 'd070ea86_nohash_3.wav', '96d8bb6f_nohash_4.wav', '0d82fd99_nohash_1.wav', 'b414c653_nohash_3.wav', '856eb138_nohash_2.wav', '7213ed54_nohash_4.wav', '3b4f8f24_nohash_2.wav', '8769c34c_nohash_3.wav', 'a05a90c1_nohash_0.wav', 'a04817c2_nohash_2.wav', 'bd76a7fd_nohash_1.wav', '2e75d37a_nohash_3.wav', '4995d875_nohash_1.wav', '2aca1e72_nohash_4.wav', '25e95412_nohash_1.wav', '85d2ac4b_nohash_1.wav', '5ebc1cda_nohash_4.wav', 'f9643d42_nohash_0.wav', '472b8045_nohash_4.wav', 'c9b5ff26_nohash_3.wav', '333d7ddb_nohash_0.wav', '2aca1e72_nohash_10.wav', '042a8dde_nohash_1.wav', 'b5cf6ea8_nohash_5.wav', 'c91dbe66_nohash_0.wav', '61ab8fbc_nohash_2.wav', '88d009d2_nohash_1.wav', 'f822b9bf_nohash_4.wav', 'd5b963aa_nohash_3.wav', '4c6167ca_nohash_0.wav', 'b0f5b16d_nohash_3.wav', '0f46028a_nohash_1.wav', '7fb8d703_nohash_4.wav', '3291330e_nohash_3.wav', '890cc926_nohash_2.wav', '67bdbf56_nohash_0.wav', '45692b02_nohash_1.wav', '06f6c194_nohash_0.wav', '3a69f765_nohash_0.wav', 'f2f0d244_nohash_2.wav', '067f61e2_nohash_0.wav', '6bf5baf3_nohash_1.wav', '7d6b4b10_nohash_0.wav', 'f9643d42_nohash_1.wav', '20a0d54b_nohash_0.wav', '42a99aec_nohash_1.wav', 'ceef6d96_nohash_3.wav', '435695e3_nohash_2.wav', '131e738d_nohash_2.wav', '0165e0e8_nohash_0.wav', 'de89e2ca_nohash_1.wav', '8f447c3e_nohash_0.wav', '0b7ee1a0_nohash_0.wav', '5ebc1cda_nohash_5.wav', 'd1dd03ed_nohash_4.wav', 'f68160c0_nohash_0.wav', '0f46028a_nohash_2.wav', 'd21fd169_nohash_4.wav', '18f8afd5_nohash_3.wav', '2aca1e72_nohash_2.wav', 'f603e3f9_nohash_0.wav', '3ce4910e_nohash_0.wav', 'fa57ab3b_nohash_3.wav', '262d7a03_nohash_1.wav', '2fcb6397_nohash_0.wav', 'e7bcee8a_nohash_0.wav', 'c50f55b8_nohash_20.wav', '7c83c5f6_nohash_1.wav', '2fee065a_nohash_3.wav', 'f9643d42_nohash_4.wav', 'c5a1e46c_nohash_3.wav', 'fb7eb481_nohash_3.wav', '3291330e_nohash_1.wav', 'f822b9bf_nohash_0.wav', '1c84a139_nohash_2.wav', 'd3d8fcd0_nohash_1.wav', '332d33b1_nohash_1.wav', 'b29f8b23_nohash_3.wav', 'ab46af55_nohash_4.wav', '5cf1ecce_nohash_2.wav', '4e6902d0_nohash_4.wav', '06f6c194_nohash_1.wav', '365908bd_nohash_2.wav', '8fe67225_nohash_0.wav', '14c7b073_nohash_4.wav', 'f250345e_nohash_0.wav', 'ccca5655_nohash_3.wav', '7213ed54_nohash_1.wav', '856eb138_nohash_1.wav', 'b308773d_nohash_3.wav', 'f736ab63_nohash_0.wav', 'cb62dbf1_nohash_1.wav', '890cc926_nohash_4.wav', 'f8ba7c0e_nohash_1.wav', 'f30285c8_nohash_4.wav', '5ebc1cda_nohash_3.wav', 'b0f5b16d_nohash_0.wav', '893705bb_nohash_6.wav', '8769c34c_nohash_1.wav', 'fb7eb481_nohash_2.wav', '9fac5701_nohash_0.wav', '3ce4910e_nohash_2.wav', '74241b28_nohash_0.wav', 'f8ba7c0e_nohash_0.wav', '29dce108_nohash_2.wav', 'd070ea86_nohash_2.wav', '9a76f8c3_nohash_4.wav', 'cd671b5f_nohash_3.wav', '89947bd7_nohash_0.wav', 'f2e59fea_nohash_2.wav', '87d5e978_nohash_4.wav', '1a994c9f_nohash_0.wav', '3b195250_nohash_4.wav', 'da040491_nohash_3.wav', '18d84076_nohash_0.wav', '1ed0b13d_nohash_0.wav', '645ed69d_nohash_3.wav', 'f5626af6_nohash_0.wav', '879a2b38_nohash_4.wav', '8dc18a75_nohash_4.wav', 'bbc30633_nohash_2.wav', '5a5721f8_nohash_0.wav', '4c3cddb8_nohash_2.wav', '1ed0b13d_nohash_4.wav', '189cbabe_nohash_4.wav', '3cc595de_nohash_1.wav', 'c7dc7278_nohash_1.wav', '890cc926_nohash_0.wav', '27c24504_nohash_0.wav', '98ea0818_nohash_0.wav', '773e26f7_nohash_3.wav', '08ab231c_nohash_2.wav', 'cdee383b_nohash_4.wav', 'b69002d4_nohash_4.wav', '676f8138_nohash_3.wav', 'ee1d8d49_nohash_1.wav', '0f7266cf_nohash_2.wav', 'f68160c0_nohash_1.wav', '1e02ffc5_nohash_2.wav', '236b6113_nohash_0.wav', 'a6f2fd71_nohash_2.wav', 'cfbedff9_nohash_2.wav', 'e3e0f145_nohash_0.wav', 'ac9dee0e_nohash_1.wav', '39b5fdab_nohash_0.wav', '332d33b1_nohash_3.wav', '4cee0c60_nohash_2.wav', 'b29f8b23_nohash_0.wav', 'db24628d_nohash_1.wav', '1e9e6bdd_nohash_4.wav', '6565a81d_nohash_4.wav', '5f9cd2eb_nohash_4.wav', '6969e51a_nohash_0.wav', '3c4aa5ef_nohash_2.wav', '2b5e346d_nohash_2.wav', 'e49428d9_nohash_1.wav', 'a2cc5444_nohash_0.wav', 'a77fbcfd_nohash_1.wav', 'ace072ba_nohash_3.wav', '72242187_nohash_3.wav', '365908bd_nohash_3.wav', '3659fc1c_nohash_0.wav', '333d7ddb_nohash_4.wav', '978240e1_nohash_4.wav', '879a2b38_nohash_2.wav', 'cdee383b_nohash_2.wav', 'de3fe344_nohash_1.wav', 'e9abfe31_nohash_0.wav', 'a7200079_nohash_3.wav', 'ae5578f4_nohash_0.wav', 'cb72dfb6_nohash_2.wav', '893705bb_nohash_4.wav', '845f8553_nohash_1.wav', '30060aba_nohash_0.wav', 'ec32860c_nohash_0.wav', 'd3831f6a_nohash_0.wav', 'c50f55b8_nohash_7.wav', '9151f184_nohash_4.wav', '23da904f_nohash_1.wav', '6124b431_nohash_2.wav', 'ab9b93e4_nohash_1.wav', 'b69fe0e2_nohash_4.wav', 'f822b9bf_nohash_2.wav', 'f01a0d63_nohash_1.wav', 'bfd26d6b_nohash_2.wav', 'f0659908_nohash_2.wav', 'a77fbcfd_nohash_2.wav', '3b3d2f59_nohash_2.wav', '79b37d3a_nohash_0.wav', 'cb72dfb6_nohash_1.wav', '92521ccc_nohash_0.wav', '25e95412_nohash_4.wav', '25e95412_nohash_5.wav', '6640fdc0_nohash_1.wav', '54ad8f22_nohash_1.wav', 'fa52ddf6_nohash_0.wav', '2f0ce4d9_nohash_1.wav', 'c50f55b8_nohash_12.wav', 'd21fd169_nohash_0.wav', 'ab9b93e4_nohash_0.wav', '9b8a7439_nohash_3.wav', 'f2e59fea_nohash_4.wav', 'bb6d4301_nohash_4.wav', 'c1cc6e95_nohash_0.wav', '878befa7_nohash_0.wav', 'eeaf97c3_nohash_3.wav', '322d17d3_nohash_3.wav', 'b44007bc_nohash_0.wav', 'fa52ddf6_nohash_1.wav', '5f01c798_nohash_1.wav', 'a73be046_nohash_0.wav', '32ad5b65_nohash_0.wav', 'b4ea0d9a_nohash_1.wav', 'e0c782d5_nohash_0.wav', '5a98d407_nohash_3.wav', 'f0522ff4_nohash_1.wav', '89947bd7_nohash_2.wav', '508e30ee_nohash_2.wav', 'fbb56351_nohash_3.wav', '1e02ffc5_nohash_0.wav', 'a929f9b9_nohash_2.wav', 'ff2b842e_nohash_4.wav', '31f01a8d_nohash_3.wav', '2f0ce4d9_nohash_2.wav', '6aa8def4_nohash_4.wav', '195c120a_nohash_2.wav', '54aecbd5_nohash_3.wav', '9b02d503_nohash_3.wav', '0c540988_nohash_0.wav', 'b69002d4_nohash_2.wav', '262d7a03_nohash_0.wav', '2fee065a_nohash_0.wav', 'e9abfe31_nohash_1.wav', 'f30285c8_nohash_1.wav', '95fd5a0f_nohash_3.wav', '0ea9c8ce_nohash_3.wav', '4d763ca4_nohash_1.wav', '13a93b33_nohash_0.wav', 'ac9dee0e_nohash_4.wav', 'f798ac78_nohash_1.wav', 'd9aa8c90_nohash_1.wav', '5d4e3bb8_nohash_0.wav', 'a929f9b9_nohash_0.wav', 'd9aa8c90_nohash_4.wav', '978240e1_nohash_2.wav', 'c4e00ee9_nohash_2.wav', '54ad8f22_nohash_3.wav', 'bdd22e4d_nohash_3.wav', '525eaa62_nohash_2.wav', 'fa52ddf6_nohash_2.wav', '31f01a8d_nohash_2.wav', '02ade946_nohash_2.wav', '226537ab_nohash_2.wav', '0cb74144_nohash_1.wav', '067f61e2_nohash_1.wav', 'ac9dee0e_nohash_0.wav', '3291330e_nohash_4.wav', 'eeaf97c3_nohash_1.wav', '80be36a2_nohash_0.wav', '837a0f64_nohash_1.wav', 'cd671b5f_nohash_4.wav', '2927c601_nohash_4.wav', '62f05757_nohash_1.wav', 'f8ba7c0e_nohash_2.wav', 'a2cc5444_nohash_2.wav', '7464b22e_nohash_0.wav', '5ebc1cda_nohash_2.wav', '2a1f4853_nohash_4.wav', '821b64cc_nohash_3.wav', '050170cb_nohash_3.wav', '1a994c9f_nohash_3.wav', '2aca1e72_nohash_13.wav', 'b91b718c_nohash_1.wav', '9b8a7439_nohash_4.wav', '57152045_nohash_5.wav', '94d370bf_nohash_3.wav', '7d6b4b10_nohash_2.wav', 'bbf38549_nohash_4.wav', '608473c9_nohash_1.wav', 'a55105d0_nohash_1.wav', '14c7b073_nohash_1.wav', '23da904f_nohash_2.wav', '542f38a2_nohash_0.wav', 'a045368c_nohash_2.wav', 'd070ea86_nohash_0.wav', '8769c34c_nohash_0.wav', 'c50f55b8_nohash_22.wav', 'b5cf6ea8_nohash_1.wav', '779de043_nohash_2.wav', '460209ac_nohash_0.wav', 'bcf614a2_nohash_1.wav', '3b3d2f59_nohash_5.wav', 'b414c653_nohash_1.wav', 'c5a1e46c_nohash_1.wav', '69a1a79f_nohash_2.wav', '8ea6dec6_nohash_0.wav', 'a55105d0_nohash_2.wav', '62f05757_nohash_3.wav', 'b0f5b16d_nohash_2.wav', 'ef77b778_nohash_1.wav', 'd070ea86_nohash_4.wav', '27c24504_nohash_1.wav', 'd5b963aa_nohash_0.wav', 'a7200079_nohash_0.wav', '226537ab_nohash_1.wav', 'ff0e27c3_nohash_1.wav', 'e6327279_nohash_3.wav', 'ee23b031_nohash_0.wav', '0e6e36c9_nohash_0.wav', '8e523821_nohash_2.wav', '676f8138_nohash_4.wav', '96d8bb6f_nohash_2.wav', 'db24628d_nohash_3.wav', '226537ab_nohash_3.wav', '3d9bbe2d_nohash_1.wav', '85d2ac4b_nohash_0.wav', 'af6fbbf5_nohash_1.wav', '542f38a2_nohash_1.wav', 'a7216980_nohash_3.wav', '7213ed54_nohash_0.wav', 'c50f55b8_nohash_3.wav', 'a1e71565_nohash_1.wav', '131e738d_nohash_1.wav', '87070229_nohash_0.wav', '676f8138_nohash_0.wav', '4c6944d6_nohash_4.wav', 'fc3ba625_nohash_1.wav', '4fd1443e_nohash_3.wav', '5769c5ab_nohash_0.wav', '63f7a489_nohash_3.wav', '2fee065a_nohash_2.wav', 'ca4912b6_nohash_0.wav', 'cc4f9250_nohash_2.wav', 'b5cf6ea8_nohash_8.wav', '189cbabe_nohash_3.wav', 'a7216980_nohash_1.wav', 'f2898d06_nohash_2.wav', '15dd287d_nohash_3.wav', 'bc999754_nohash_0.wav', '87d5e978_nohash_0.wav', '3a69f765_nohash_1.wav', '74241b28_nohash_2.wav', 'e3e0f145_nohash_4.wav', '171edea9_nohash_0.wav', '472b8045_nohash_3.wav', '51c5601d_nohash_4.wav', '879a2b38_nohash_0.wav', 'de3fe344_nohash_2.wav', '08ab231c_nohash_4.wav', '9307154f_nohash_0.wav', '15dd287d_nohash_2.wav', '54aecbd5_nohash_2.wav', '87070229_nohash_2.wav', '890cc926_nohash_1.wav', '513aeddf_nohash_3.wav', '51c5601d_nohash_0.wav', '5769c5ab_nohash_2.wav', '3589bc72_nohash_0.wav', '3d9bbe2d_nohash_0.wav', '674ca5ea_nohash_0.wav', '1e9e6bdd_nohash_1.wav', '4c3cddb8_nohash_3.wav', '5b32733e_nohash_0.wav', 'a4383927_nohash_0.wav', '878befa7_nohash_3.wav', 'c50f55b8_nohash_10.wav', '131e738d_nohash_4.wav', '9448c397_nohash_4.wav', 'eeaf97c3_nohash_0.wav', '29229c21_nohash_4.wav', '0f7266cf_nohash_3.wav', 'f2e59fea_nohash_0.wav', 'b4ea0d9a_nohash_2.wav', '29dce108_nohash_1.wav', '14c7b073_nohash_3.wav', 'bdd22e4d_nohash_2.wav', 'b6573c88_nohash_1.wav', '9be15e93_nohash_2.wav', '3a3ee7ed_nohash_0.wav', 'e4be0cf6_nohash_1.wav', 'a16013b7_nohash_4.wav', 'c678e0b3_nohash_0.wav', '23da904f_nohash_4.wav', '95fd5a0f_nohash_5.wav', '27c24504_nohash_2.wav', 'b4ea0d9a_nohash_4.wav', 'c351e611_nohash_1.wav', '3a3ee7ed_nohash_2.wav', '674ca5ea_nohash_3.wav', '61ab8fbc_nohash_3.wav', 'cc4f9250_nohash_3.wav', 'a9ca1818_nohash_2.wav', 'ca4912b6_nohash_4.wav', '18e910f4_nohash_1.wav', '513aeddf_nohash_0.wav', '3102f006_nohash_2.wav', '525eaa62_nohash_3.wav', '64a80906_nohash_1.wav', 'db24628d_nohash_2.wav', '779de043_nohash_0.wav', '333d7ddb_nohash_2.wav', '050170cb_nohash_1.wav', '7d4beb11_nohash_0.wav', '23da904f_nohash_0.wav', '578d3efb_nohash_1.wav', 'fbb2f6cc_nohash_0.wav', 'b0f5b16d_nohash_1.wav', '3b3d2f59_nohash_3.wav', 'ef3367d9_nohash_3.wav', '845f8553_nohash_2.wav', 'ccca5655_nohash_2.wav', '513aeddf_nohash_1.wav', 'cdee383b_nohash_3.wav', '2aca1e72_nohash_12.wav', 'd5b963aa_nohash_4.wav', '2f0ce4d9_nohash_0.wav', '113b3fbc_nohash_2.wav', '5f9cd2eb_nohash_1.wav', '94d370bf_nohash_1.wav', 'a293e285_nohash_0.wav', 'c7dc7278_nohash_3.wav', 'ca4912b6_nohash_2.wav', 'bdd22e4d_nohash_4.wav', '13dce503_nohash_0.wav', '1970b130_nohash_0.wav', '70880cc6_nohash_0.wav', 'fc3ba625_nohash_3.wav', '6ef407da_nohash_3.wav', 'cfbedff9_nohash_3.wav', '61e2f74f_nohash_1.wav', '73f20b00_nohash_0.wav', '14c7b073_nohash_0.wav', '42f81601_nohash_1.wav', 'beb458a4_nohash_2.wav', '7622d95b_nohash_0.wav', '5170b77f_nohash_2.wav', '333d7ddb_nohash_1.wav', '5a98d407_nohash_0.wav', 'c50f55b8_nohash_16.wav', '6640fdc0_nohash_0.wav', 'd4dddb92_nohash_0.wav', 'ce0cb033_nohash_3.wav', '40738a2d_nohash_0.wav', '676f8138_nohash_2.wav', 'af54ec46_nohash_0.wav', '2fcb6397_nohash_1.wav', '674ca5ea_nohash_1.wav', 'bd76a7fd_nohash_3.wav', 'c2dccf38_nohash_1.wav', '15dd287d_nohash_1.wav', '42f81601_nohash_3.wav', '4c3cddb8_nohash_0.wav', 'fd5ccd39_nohash_1.wav', 'bbf38549_nohash_1.wav', 'bd76a7fd_nohash_4.wav', '525eaa62_nohash_1.wav', '3d86b69a_nohash_2.wav', '2aca1e72_nohash_6.wav', '0d85a428_nohash_0.wav', 'd5b963aa_nohash_1.wav', '32ad5b65_nohash_4.wav', '1e9e6bdd_nohash_3.wav', 'fc3ba625_nohash_4.wav', '856eb138_nohash_3.wav', '29229c21_nohash_2.wav', 'b308773d_nohash_4.wav', '4fd1443e_nohash_0.wav', 'ed032775_nohash_4.wav', 'cb72dfb6_nohash_4.wav', 'd0745d72_nohash_1.wav', '70b0ccf4_nohash_0.wav', 'a7200079_nohash_4.wav', '30276d03_nohash_0.wav', '3d794813_nohash_4.wav', '63f7a489_nohash_2.wav', '3a69f765_nohash_3.wav', 'd9aa8c90_nohash_3.wav', '24a3e589_nohash_1.wav', '9a2e5b3c_nohash_0.wav', '559bc36a_nohash_0.wav', '9f93e408_nohash_3.wav', '30f6e665_nohash_0.wav', '967ad5ef_nohash_0.wav', 'f01a0d63_nohash_4.wav', 'cc3b5b62_nohash_0.wav', '8dc18a75_nohash_2.wav', '6aa8def4_nohash_0.wav', '61e2f74f_nohash_2.wav', '017c4098_nohash_3.wav', 'da040491_nohash_0.wav', '15dd287d_nohash_0.wav', 'ac9dee0e_nohash_2.wav', '1b42b551_nohash_0.wav', '7f581e94_nohash_0.wav', 'da040491_nohash_4.wav', 'e9abfe31_nohash_3.wav', '3d86b69a_nohash_0.wav', '3291330e_nohash_0.wav', '4c6167ca_nohash_1.wav', 'acb9db68_nohash_0.wav', '81332c92_nohash_1.wav', 'ed032775_nohash_0.wav', 'b5cf6ea8_nohash_0.wav', 'e11fbc6e_nohash_1.wav', 'ace072ba_nohash_0.wav', '4e61bf96_nohash_0.wav', 'ec989d6d_nohash_2.wav', 'c633a455_nohash_0.wav', 'a489191a_nohash_3.wav', '18f8afd5_nohash_0.wav', 'e0c782d5_nohash_2.wav', 'c50f55b8_nohash_0.wav', 'e71a9381_nohash_2.wav', 'c0e3ff37_nohash_0.wav', 'f68160c0_nohash_3.wav', 'd1526c4e_nohash_0.wav', '617aeb6c_nohash_2.wav', '62ccd358_nohash_1.wav', '30276d03_nohash_2.wav', 'f5626af6_nohash_3.wav', '4e99c1b7_nohash_0.wav', 'e882abb2_nohash_3.wav', '73f20b00_nohash_2.wav', 'a928cc5b_nohash_1.wav', '24cab2cb_nohash_0.wav', 'af6fbbf5_nohash_2.wav', 'a05a90c1_nohash_2.wav', '189cbabe_nohash_2.wav', '9be15e93_nohash_0.wav', '9448c397_nohash_0.wav', '645ed69d_nohash_1.wav', '5170b77f_nohash_0.wav', 'acfd5b5e_nohash_4.wav', '39833acb_nohash_4.wav', 'c4e00ee9_nohash_0.wav', '211b928a_nohash_4.wav', '3291330e_nohash_2.wav', 'c50f55b8_nohash_5.wav', '5bf1f1cb_nohash_0.wav', 'a489191a_nohash_2.wav', 'f2898d06_nohash_4.wav', 'cc4f9250_nohash_1.wav', 'd21fd169_nohash_3.wav', '5f9cd2eb_nohash_2.wav', 'fbb56351_nohash_2.wav', '2fcb6397_nohash_3.wav', 'beb458a4_nohash_3.wav', 'ad526ada_nohash_0.wav', 'a77fbcfd_nohash_0.wav', '2aca1e72_nohash_8.wav', '679463fc_nohash_2.wav', '5ebc1cda_nohash_6.wav', '1496195a_nohash_3.wav', '25e95412_nohash_3.wav', '91b03183_nohash_0.wav', 'eaa83485_nohash_3.wav', 'd070ea86_nohash_1.wav', 'aa80f517_nohash_4.wav', '0b7ee1a0_nohash_3.wav', '728be664_nohash_0.wav', 'f798ac78_nohash_2.wav', '85851131_nohash_4.wav', 'bb05582b_nohash_1.wav', '61e2f74f_nohash_3.wav', '98ea0818_nohash_1.wav', 'a7200079_nohash_2.wav', 'f8ba7c0e_nohash_3.wav', 'd394ef8e_nohash_0.wav', '85ac0c1b_nohash_0.wav', '773e26f7_nohash_0.wav', 'beb458a4_nohash_1.wav', 'cb62dbf1_nohash_3.wav', '3a53b856_nohash_0.wav', '773e26f7_nohash_1.wav', 'd3831f6a_nohash_3.wav', 'd1dd03ed_nohash_2.wav', '89947bd7_nohash_1.wav', '0d6d7360_nohash_4.wav', 'a16013b7_nohash_2.wav', 'b8874962_nohash_2.wav', 'fb8c31a9_nohash_1.wav', '57152045_nohash_1.wav', 'c50f55b8_nohash_14.wav', '6aa8def4_nohash_2.wav', '3d86b69a_nohash_1.wav', '235b444f_nohash_3.wav', '0a2b400e_nohash_3.wav', '5f1253e9_nohash_0.wav', 'eda072b5_nohash_0.wav', '508e30ee_nohash_1.wav', 'c50f55b8_nohash_15.wav', 'cc4f9250_nohash_0.wav', '1c84a139_nohash_3.wav', '616420be_nohash_1.wav', '1a994c9f_nohash_1.wav', 'c351e611_nohash_0.wav', '113b3fbc_nohash_4.wav', 'c2657ba5_nohash_1.wav', 'ab46af55_nohash_3.wav', 'c0cb43d6_nohash_1.wav', '29229c21_nohash_1.wav', '3b3d2f59_nohash_1.wav', 'd394ef8e_nohash_4.wav', 'fd9c7413_nohash_1.wav', '29dce108_nohash_0.wav', '64e48f55_nohash_2.wav', 'ef3367d9_nohash_6.wav', '7f208e83_nohash_0.wav', '7f208e83_nohash_1.wav', 'ff2b842e_nohash_3.wav', '08ab231c_nohash_1.wav', '0e8ec1cb_nohash_0.wav', '3b195250_nohash_3.wav', '042a8dde_nohash_0.wav', '72242187_nohash_2.wav', '2fcb6397_nohash_2.wav', '879a2b38_nohash_1.wav', '25e95412_nohash_0.wav', '7fb8d703_nohash_0.wav', '0d6d7360_nohash_3.wav', '3c4aa5ef_nohash_1.wav', 'f568162b_nohash_1.wav', '7e7ca854_nohash_0.wav', 'f68160c0_nohash_2.wav', 'c351e611_nohash_2.wav', 'f5341341_nohash_2.wav', 'f2e9b610_nohash_2.wav', '74241b28_nohash_3.wav', 'a7acbbeb_nohash_2.wav', 'af6fbbf5_nohash_0.wav', 'ff0e27c3_nohash_0.wav', 'b29f8b23_nohash_2.wav', 'f736ab63_nohash_1.wav', '2b5e346d_nohash_0.wav', 'ceef6d96_nohash_1.wav', '51c5601d_nohash_3.wav', 'a05a90c1_nohash_3.wav', 'f0522ff4_nohash_3.wav', '2aca1e72_nohash_9.wav', '40738a2d_nohash_2.wav', '69a1a79f_nohash_0.wav', '3b3d2f59_nohash_0.wav', '9151f184_nohash_3.wav', '4c6944d6_nohash_1.wav', '1a0f9c63_nohash_0.wav', '3108acca_nohash_3.wav', 'b69fe0e2_nohash_2.wav', '39833acb_nohash_1.wav', '15dd287d_nohash_4.wav', '3b4f8f24_nohash_0.wav', '1970b130_nohash_1.wav', '3d9bbe2d_nohash_2.wav', '3c4aa5ef_nohash_4.wav', '1acc97de_nohash_1.wav', 'c0e3ff37_nohash_1.wav', '578d3efb_nohash_0.wav', '679463fc_nohash_0.wav', '1dc86f91_nohash_1.wav', 'c4e00ee9_nohash_1.wav', 'f30285c8_nohash_3.wav', '9bfd6a9d_nohash_0.wav', 'f01a0d63_nohash_2.wav', '2e75d37a_nohash_0.wav', '3a929277_nohash_1.wav', '31f01a8d_nohash_1.wav', '81332c92_nohash_0.wav', '4fce7686_nohash_1.wav', '1a73dcd1_nohash_0.wav', '51c5601d_nohash_2.wav', '171edea9_nohash_3.wav', '0cb74144_nohash_0.wav', '5ebc1cda_nohash_0.wav', '29229c21_nohash_3.wav', 'ef77b778_nohash_2.wav', '5c43ac9f_nohash_0.wav', 'eaa83485_nohash_1.wav', 'a9ca1818_nohash_3.wav', '8b25410a_nohash_2.wav', '85851131_nohash_1.wav', 'f2898d06_nohash_1.wav', '5087f68b_nohash_0.wav', 'b91b718c_nohash_0.wav', '3a69f765_nohash_4.wav', 'd0745d72_nohash_0.wav', 'b528edb3_nohash_3.wav', '2b5e346d_nohash_1.wav', 'f035e2ea_nohash_0.wav', '29dce108_nohash_3.wav', 'ce0cb033_nohash_2.wav', '3a53b856_nohash_1.wav', 'ddedba85_nohash_2.wav', '189cbabe_nohash_1.wav', 'b528edb3_nohash_2.wav', '5cf1ecce_nohash_0.wav', 'de89e2ca_nohash_3.wav', 'ed032775_nohash_3.wav', '0d6d7360_nohash_0.wav', '5f9cd2eb_nohash_0.wav', '1e02ffc5_nohash_1.wav', '679463fc_nohash_3.wav', '02ade946_nohash_3.wav', '18e910f4_nohash_2.wav', 'f8ba7c0e_nohash_4.wav', '18e910f4_nohash_0.wav', '7d6b4b10_nohash_3.wav', 'b528edb3_nohash_1.wav', 'bd76a7fd_nohash_6.wav', 'a2d61879_nohash_0.wav', '3b4f8f24_nohash_1.wav', 'f035e2ea_nohash_4.wav', 'ac9dee0e_nohash_3.wav', '57152045_nohash_0.wav', '6bf5baf3_nohash_0.wav', '0f46028a_nohash_0.wav', 'a1e71565_nohash_0.wav', '339f2c5c_nohash_0.wav', 'a9ca1818_nohash_4.wav', '508e30ee_nohash_4.wav', 'f2f0d244_nohash_1.wav', '3589bc72_nohash_3.wav', '0d6d7360_nohash_1.wav', '2748cce7_nohash_0.wav', '9151f184_nohash_1.wav', '7d6b4b10_nohash_1.wav', 'e71a9381_nohash_1.wav', '235b444f_nohash_1.wav', '88b7c5fa_nohash_0.wav', 'fb7eb481_nohash_1.wav', 'bb05582b_nohash_0.wav', 'b5cf6ea8_nohash_9.wav', '256c0a05_nohash_2.wav', '9151f184_nohash_0.wav', '3a3ee7ed_nohash_1.wav', '3bb68054_nohash_2.wav', '9a76f8c3_nohash_1.wav', '9a76f8c3_nohash_3.wav', 'f035e2ea_nohash_2.wav', 'f736ab63_nohash_4.wav', '1589451d_nohash_1.wav', 'c50f55b8_nohash_2.wav', 'ccca5655_nohash_4.wav', 'cdee383b_nohash_1.wav', '5a98d407_nohash_1.wav', 'd1dd03ed_nohash_0.wav', 'd21fd169_nohash_2.wav', '5f9cd2eb_nohash_5.wav', '2927c601_nohash_2.wav', 'b76f6088_nohash_3.wav', 'bcf614a2_nohash_2.wav', 'd264f7b6_nohash_3.wav', '3d794813_nohash_2.wav', 'a56859ea_nohash_1.wav', 'da040491_nohash_1.wav', 'f5341341_nohash_1.wav', 'ff2b842e_nohash_0.wav', '3102f006_nohash_3.wav', '821b64cc_nohash_2.wav', 'ef77b778_nohash_0.wav', '893705bb_nohash_1.wav', '617aeb6c_nohash_1.wav', 'f5341341_nohash_0.wav', '2a1f4853_nohash_0.wav', '4d763ca4_nohash_0.wav', '2a1f4853_nohash_3.wav', '0ba018fc_nohash_0.wav', 'dae01802_nohash_3.wav', '171edea9_nohash_4.wav', 'fbb56351_nohash_4.wav', '978240e1_nohash_1.wav', 'acfd5b5e_nohash_0.wav', '0a5636ca_nohash_0.wav', '3102f006_nohash_1.wav', 'b414c653_nohash_2.wav', '98ea0818_nohash_4.wav', 'f0522ff4_nohash_0.wav', 'e6327279_nohash_4.wav', '80768fa5_nohash_0.wav', '6565a81d_nohash_2.wav', 'fa52ddf6_nohash_4.wav', '617aeb6c_nohash_3.wav', 'd3d8fcd0_nohash_0.wav', '73f20b00_nohash_1.wav', '9f93e408_nohash_2.wav', 'f2898d06_nohash_3.wav', '332d33b1_nohash_0.wav', '3b4f8f24_nohash_4.wav', 'bfd26d6b_nohash_1.wav', 'a05a90c1_nohash_4.wav', 'f798ac78_nohash_0.wav', '72e382bd_nohash_3.wav', '1a994c9f_nohash_2.wav', 'f568162b_nohash_0.wav', '7c83c5f6_nohash_2.wav', '195c120a_nohash_0.wav', '72e382bd_nohash_2.wav', 'c98bbbd3_nohash_0.wav', '5d4e3bb8_nohash_1.wav', '435695e3_nohash_3.wav', '1496195a_nohash_0.wav', '29229c21_nohash_0.wav', 'fb8c31a9_nohash_4.wav', '64df20d8_nohash_1.wav', 'd394ef8e_nohash_1.wav', '18f8afd5_nohash_4.wav', '5a5721f8_nohash_4.wav', 'a04817c2_nohash_1.wav', '90e72357_nohash_3.wav', '0f7266cf_nohash_0.wav', 'bcf614a2_nohash_0.wav', '1c76f5f3_nohash_0.wav', '0585b66d_nohash_3.wav', 'c50f55b8_nohash_13.wav', 'bd76a7fd_nohash_0.wav', 'ccca5655_nohash_1.wav', '211b928a_nohash_2.wav', 'f1eaff75_nohash_0.wav', '1c84a139_nohash_0.wav', '7c86c03e_nohash_1.wav', '332d33b1_nohash_2.wav', 'fa52ddf6_nohash_3.wav', '42398aab_nohash_0.wav', '7213ed54_nohash_3.wav', '645ed69d_nohash_2.wav', 'a4383927_nohash_1.wav', '8dc18a75_nohash_3.wav', '31db232b_nohash_1.wav', '978240e1_nohash_0.wav', '0585b66d_nohash_1.wav', '85851131_nohash_0.wav', 'eeaf97c3_nohash_4.wav', '32ad5b65_nohash_3.wav', '5f9cd2eb_nohash_3.wav', 'fa57ab3b_nohash_2.wav', 'f0522ff4_nohash_2.wav', '7e7ca854_nohash_3.wav', 'b5cf6ea8_nohash_6.wav', '821b64cc_nohash_1.wav', '85851131_nohash_3.wav', 'c53e1048_nohash_0.wav', 'b69002d4_nohash_1.wav', '3f45a0cf_nohash_0.wav', 'd264f7b6_nohash_1.wav', '3589bc72_nohash_1.wav', '2aca1e72_nohash_7.wav', '578d3efb_nohash_4.wav', '13dce503_nohash_1.wav', 'fa57ab3b_nohash_0.wav', '82951cf0_nohash_0.wav', 'bb6d4301_nohash_0.wav', '0e6e36c9_nohash_2.wav', 'f2f0d244_nohash_3.wav', 'e1acea44_nohash_0.wav', '893705bb_nohash_0.wav', '674ca5ea_nohash_2.wav', '7622d95b_nohash_1.wav', '5a98d407_nohash_4.wav', '5ebc1cda_nohash_1.wav', 'cc8b3228_nohash_0.wav', '96d8bb6f_nohash_3.wav', '559bc36a_nohash_1.wav', '62f05757_nohash_0.wav', '5170b77f_nohash_3.wav', 'f1d8a638_nohash_2.wav', '2fee065a_nohash_1.wav', 'b8874962_nohash_4.wav', '4e99c1b7_nohash_1.wav', 'e9bc5cc2_nohash_0.wav', '0d90d8e1_nohash_2.wav', 'db24628d_nohash_0.wav', '3ce4910e_nohash_3.wav', '62f05757_nohash_2.wav', '08ab231c_nohash_3.wav', 'fc3ba625_nohash_0.wav', 'bde0f20a_nohash_4.wav', '3b195250_nohash_0.wav', 'bbc30633_nohash_0.wav', '578d3efb_nohash_2.wav', '4c3cddb8_nohash_1.wav', '96d8bb6f_nohash_0.wav', 'e882abb2_nohash_2.wav', '067f61e2_nohash_2.wav', 'de3fe344_nohash_3.wav', 'f736ab63_nohash_2.wav', '3d86b69a_nohash_3.wav', '94d370bf_nohash_0.wav', 'f5626af6_nohash_1.wav', '856eb138_nohash_0.wav', '42a99aec_nohash_0.wav', 'bbf38549_nohash_0.wav', '73f20b00_nohash_3.wav', 'f01a0d63_nohash_3.wav', '6fb3d5a7_nohash_1.wav', 'c9b5ff26_nohash_0.wav', 'e11fbc6e_nohash_2.wav', 'f2e59fea_nohash_1.wav', '51f7a034_nohash_1.wav', '63ae15e4_nohash_1.wav', '9b02d503_nohash_0.wav', '7213ed54_nohash_2.wav', '6565a81d_nohash_3.wav', '90e72357_nohash_2.wav', 'd962e5ac_nohash_1.wav', 'cb62dbf1_nohash_2.wav', '050170cb_nohash_0.wav', '616420be_nohash_3.wav', '03401e93_nohash_0.wav', '171edea9_nohash_2.wav', '02ade946_nohash_0.wav', '87d5e978_nohash_1.wav', '13dce503_nohash_2.wav', '067f61e2_nohash_4.wav', '0a2b400e_nohash_0.wav', 'f68160c0_nohash_4.wav', 'ec9b830b_nohash_1.wav', '893705bb_nohash_7.wav', '9e92ef0c_nohash_0.wav', '365908bd_nohash_1.wav', '31db232b_nohash_0.wav', 'c50f55b8_nohash_18.wav', 'af790082_nohash_1.wav', 'f0659908_nohash_3.wav', '23add12a_nohash_0.wav', 'b089169d_nohash_0.wav', 'a73be046_nohash_1.wav', '72e382bd_nohash_1.wav', 'c5a1e46c_nohash_2.wav', 'ace072ba_nohash_2.wav', '91b03183_nohash_1.wav', '5a98d407_nohash_2.wav', '81332c92_nohash_3.wav', '234d6a48_nohash_3.wav', 'b5cf6ea8_nohash_2.wav', 'ca4d5368_nohash_1.wav', '79903546_nohash_1.wav', '4cee0c60_nohash_1.wav', '0b7ee1a0_nohash_2.wav', '51f7a034_nohash_2.wav', '131e738d_nohash_3.wav', 'fbb2f6cc_nohash_1.wav', 'ff4ed4f3_nohash_1.wav', '893705bb_nohash_2.wav', '5769c5ab_nohash_3.wav', '5f01c798_nohash_0.wav', '4c6944d6_nohash_0.wav', '8b25410a_nohash_4.wav', '3d794813_nohash_3.wav', '90735d8b_nohash_0.wav', '39833acb_nohash_2.wav', '30060aba_nohash_1.wav', '24a3e589_nohash_3.wav', 'a045368c_nohash_3.wav', '8769c34c_nohash_2.wav', 'b528edb3_nohash_0.wav', 'c50f55b8_nohash_1.wav', 'b69002d4_nohash_3.wav', 'fa57ab3b_nohash_4.wav', '312b96ec_nohash_0.wav', '856eb138_nohash_4.wav', 'b69fe0e2_nohash_1.wav', 'ebdd0f59_nohash_0.wav', 'f798ac78_nohash_3.wav', '4995d875_nohash_2.wav', '24cab2cb_nohash_1.wav', '8e523821_nohash_3.wav', 'bfd26d6b_nohash_0.wav', 'e0c782d5_nohash_1.wav', 'fbb2f6cc_nohash_2.wav', '0585b66d_nohash_2.wav', '40738a2d_nohash_1.wav', 'e3e0f145_nohash_1.wav', '69a1a79f_nohash_4.wav', 'e4be0cf6_nohash_0.wav', 'cfbedff9_nohash_1.wav', 'bb6d4301_nohash_2.wav', 'a2cc5444_nohash_1.wav', 'a56859ea_nohash_0.wav', '5f5eef60_nohash_1.wav', '08ab231c_nohash_0.wav', 'f2e9b610_nohash_1.wav', '87d5e978_nohash_3.wav', 'b76f6088_nohash_2.wav', 'e4be0cf6_nohash_4.wav', '0e6e36c9_nohash_1.wav', '1a0f9c63_nohash_1.wav', 'c50f55b8_nohash_17.wav', '06f6c194_nohash_2.wav', '435695e3_nohash_0.wav', '8fe67225_nohash_3.wav', '893705bb_nohash_5.wav', 'a16013b7_nohash_0.wav', 'de89e2ca_nohash_4.wav', '4e6902d0_nohash_2.wav', '2fcb6397_nohash_4.wav', 'ff4ed4f3_nohash_0.wav', 'f2e9b610_nohash_4.wav', '63f7a489_nohash_1.wav', '2748cce7_nohash_1.wav', 'd962e5ac_nohash_3.wav', 'e6327279_nohash_1.wav', 'a55105d0_nohash_4.wav', '8b25410a_nohash_0.wav', '42f81601_nohash_4.wav', 'cc8b3228_nohash_3.wav', '45692b02_nohash_2.wav', '4c6944d6_nohash_3.wav', 'e882abb2_nohash_4.wav', '3a929277_nohash_2.wav', '616420be_nohash_4.wav', '6fb3d5a7_nohash_2.wav', '878befa7_nohash_1.wav', '559bc36a_nohash_2.wav', 'f01a0d63_nohash_0.wav', 'bb05582b_nohash_3.wav', '322d17d3_nohash_2.wav', '5170b77f_nohash_4.wav', 'f9643d42_nohash_2.wav', '64e48f55_nohash_0.wav', '61ab8fbc_nohash_0.wav', 'f5626af6_nohash_2.wav', 'f0659908_nohash_0.wav', 'e9bc5cc2_nohash_1.wav', 'a6f2fd71_nohash_3.wav', '616420be_nohash_0.wav', '837a0f64_nohash_2.wav', '63f7a489_nohash_4.wav', 'acfd5b5e_nohash_1.wav', 'e6327279_nohash_0.wav', '0ea9c8ce_nohash_0.wav', '779de043_nohash_1.wav', 'ccca5655_nohash_0.wav', '3b3d2f59_nohash_4.wav', 'bd76a7fd_nohash_5.wav', '211b928a_nohash_3.wav', '017c4098_nohash_4.wav', '879a2b38_nohash_3.wav', '9448c397_nohash_1.wav', 'fd5ccd39_nohash_2.wav', '525eaa62_nohash_4.wav', '23add12a_nohash_1.wav', '6ef407da_nohash_1.wav', 'bd76a7fd_nohash_2.wav', '978240e1_nohash_3.wav', '893705bb_nohash_3.wav', '02ade946_nohash_4.wav', 'c2657ba5_nohash_0.wav', '3108acca_nohash_2.wav', 'bb05582b_nohash_4.wav', 'bbc30633_nohash_3.wav', 'cd671b5f_nohash_1.wav', '7f9eb952_nohash_1.wav', '322d17d3_nohash_1.wav', '06f6c194_nohash_3.wav', 'a7216980_nohash_4.wav', '91ffb786_nohash_1.wav', 'a1e71565_nohash_2.wav', '6565a81d_nohash_1.wav', '365908bd_nohash_0.wav', '893b3c11_nohash_0.wav', 'de89e2ca_nohash_0.wav', 'aa80f517_nohash_2.wav', '6ef407da_nohash_4.wav', 'bde0f20a_nohash_2.wav', 'ef3367d9_nohash_5.wav', 'cdee383b_nohash_0.wav', 'f035e2ea_nohash_1.wav', '54aecbd5_nohash_1.wav', 'a77fbcfd_nohash_3.wav', '87070229_nohash_1.wav', '88e730cd_nohash_0.wav', '73f20b00_nohash_4.wav', '72242187_nohash_1.wav', '18ffa72d_nohash_0.wav', '64e48f55_nohash_3.wav', 'b8874962_nohash_3.wav', 'db24628d_nohash_4.wav', 'ace072ba_nohash_1.wav', '9b02d503_nohash_1.wav', '1b42b551_nohash_2.wav', 'fb8c31a9_nohash_2.wav', 'a929f9b9_nohash_3.wav', '5769c5ab_nohash_1.wav', '0585b66d_nohash_4.wav', 'a045368c_nohash_0.wav', '0cb74144_nohash_2.wav', 'cd671b5f_nohash_2.wav', '8e523821_nohash_4.wav', '3ce4910e_nohash_1.wav', '69a1a79f_nohash_1.wav', 'c50f55b8_nohash_11.wav', '3d9bbe2d_nohash_4.wav', 'b69fe0e2_nohash_0.wav', 'b4ea0d9a_nohash_3.wav', '3a929277_nohash_3.wav', '45692b02_nohash_0.wav', '24a3e589_nohash_0.wav', '1dc86f91_nohash_3.wav', 'f1d8a638_nohash_0.wav', '9448c397_nohash_3.wav', '435695e3_nohash_1.wav', 'c50f55b8_nohash_21.wav', '06f6c194_nohash_4.wav', '3a929277_nohash_0.wav', 'ad526ada_nohash_1.wav', 'c9b5ff26_nohash_4.wav', '23da904f_nohash_3.wav', 'ca4d5368_nohash_0.wav', '322d17d3_nohash_0.wav', 'c351e611_nohash_3.wav', 'de3fe344_nohash_4.wav', 'ce0cb033_nohash_0.wav', '6bf5baf3_nohash_3.wav', '042a8dde_nohash_2.wav', 'e2633cf5_nohash_0.wav', '98ea0818_nohash_3.wav', '050170cb_nohash_2.wav', 'b76f6088_nohash_1.wav', '2748cce7_nohash_2.wav', 'ee1d8d49_nohash_3.wav', 'a77fbcfd_nohash_4.wav', '4fce7686_nohash_0.wav', 'e9abfe31_nohash_2.wav', 'd394ef8e_nohash_2.wav', '4fd1443e_nohash_4.wav', 'a489191a_nohash_0.wav', '7e7ca854_nohash_1.wav', '51f7a034_nohash_0.wav', '042a8dde_nohash_3.wav', 'c50f55b8_nohash_4.wav', 'cb62dbf1_nohash_4.wav', 'ceef6d96_nohash_4.wav', 'bde0f20a_nohash_1.wav', '0e6e36c9_nohash_3.wav', 'ffea4a57_nohash_0.wav', 'c5a1e46c_nohash_0.wav', '6aa8def4_nohash_3.wav', '1474273a_nohash_0.wav', 'bdd22e4d_nohash_1.wav', 'beb458a4_nohash_0.wav', 'af790082_nohash_0.wav', '9fa86a74_nohash_1.wav', '5a5721f8_nohash_3.wav', 'f035e2ea_nohash_3.wav', '171edea9_nohash_1.wav', '4995d875_nohash_0.wav', '61ab8fbc_nohash_4.wav', '3f45a0cf_nohash_2.wav', '30276d03_nohash_1.wav', '3bb68054_nohash_0.wav', 'b308773d_nohash_0.wav', 'd9aa8c90_nohash_2.wav', 'e3e0f145_nohash_2.wav', '18f8afd5_nohash_2.wav', 'bbc30633_nohash_1.wav', '9a76f8c3_nohash_2.wav', '2e75d37a_nohash_1.wav', '2aca1e72_nohash_0.wav', 'fbb2f6cc_nohash_3.wav', '3b4f8f24_nohash_3.wav', '0d82fd99_nohash_0.wav', '4e61bf96_nohash_1.wav', '0ea9c8ce_nohash_2.wav', '64a80906_nohash_0.wav', '6c9a1ac2_nohash_0.wav', '95fd5a0f_nohash_2.wav', '2aca1e72_nohash_11.wav', '14c7b073_nohash_2.wav', '79903546_nohash_0.wav', '8fe67225_nohash_4.wav', '845f8553_nohash_3.wav', '66e8a4ec_nohash_0.wav', 'fb8c31a9_nohash_0.wav', 'ed032775_nohash_2.wav', 'c2dccf38_nohash_0.wav', 'b69002d4_nohash_0.wav', '57152045_nohash_3.wav', 'ef77b778_nohash_3.wav', '81332c92_nohash_4.wav', '39833acb_nohash_3.wav', 'acfd5b5e_nohash_2.wav', '4c6944d6_nohash_2.wav', 'a6f2fd71_nohash_0.wav', 'd0fb9ff4_nohash_0.wav', 'cd671b5f_nohash_0.wav', 'fb7008b0_nohash_1.wav', 'a045368c_nohash_4.wav', '39833acb_nohash_0.wav', '1474273a_nohash_1.wav', '6ef407da_nohash_2.wav', '5cf1ecce_nohash_1.wav', 'e9abfe31_nohash_4.wav', '017c4098_nohash_2.wav', '1e9e6bdd_nohash_2.wav', 'cb62dbf1_nohash_0.wav', '1496195a_nohash_1.wav', '2fee065a_nohash_4.wav', 'f30285c8_nohash_2.wav', '1e02ffc5_nohash_4.wav', '3a3ee7ed_nohash_4.wav', '3108acca_nohash_0.wav', '3c4aa5ef_nohash_3.wav', 'ddedba85_nohash_0.wav', '1dc86f91_nohash_4.wav', 'a2cc5444_nohash_3.wav', '3d9bbe2d_nohash_3.wav', 'ec989d6d_nohash_3.wav', 'd5b963aa_nohash_2.wav', '95fd5a0f_nohash_4.wav', '2356b88d_nohash_0.wav', '8b25410a_nohash_1.wav', '779de043_nohash_4.wav', 'ce0cb033_nohash_1.wav', 'c9b5ff26_nohash_1.wav', '9fac5701_nohash_4.wav', 'fb7008b0_nohash_0.wav', '0ba018fc_nohash_2.wav', '508e30ee_nohash_3.wav', '5f5eef60_nohash_3.wav', 'a04817c2_nohash_3.wav', '256c0a05_nohash_1.wav', '2e75d37a_nohash_2.wav', 'b2ae3928_nohash_2.wav', 'fd5ccd39_nohash_3.wav', 'a55105d0_nohash_0.wav', 'a05a90c1_nohash_1.wav', 'fbb56351_nohash_0.wav', '6bf5baf3_nohash_4.wav', 'a7216980_nohash_2.wav', '2a1f4853_nohash_1.wav', '3cc595de_nohash_3.wav'], ['1e4064b8_nohash_1.wav', '4407ba92_nohash_1.wav', '4620dc14_nohash_0.wav', '3ca784ec_nohash_0.wav', 'b12bef84_nohash_0.wav', 'c9e251d2_nohash_1.wav', 'a16b3102_nohash_1.wav', '80c17118_nohash_1.wav', 'ace82a68_nohash_0.wav', '8134f43f_nohash_0.wav', 'c885a039_nohash_0.wav', '364c0853_nohash_0.wav', '57376a4c_nohash_0.wav', 'e4b02540_nohash_0.wav', 'd98dd124_nohash_0.wav', '51995cea_nohash_0.wav', '6ef407da_nohash_0.wav', '9f93e408_nohash_0.wav', '4e6902d0_nohash_0.wav', 'a7acbbeb_nohash_0.wav', '686d030b_nohash_0.wav', '4a294341_nohash_0.wav', '4c13fe25_nohash_1.wav', '6adb8ad9_nohash_0.wav', 'cc592808_nohash_3.wav', '6b81fead_nohash_1.wav', '784e281a_nohash_0.wav', '8442ea62_nohash_1.wav', '93ec8b84_nohash_0.wav', '6414258b_nohash_1.wav', '01bcfc0c_nohash_0.wav', '173ce2be_nohash_0.wav', '7257420c_nohash_0.wav', '953fe1ad_nohash_0.wav', '3d53244b_nohash_0.wav', '50d1c8e3_nohash_0.wav', 'f292725f_nohash_0.wav', 'a24582a0_nohash_0.wav', '5b1db3ee_nohash_3.wav', 'f35eedd7_nohash_1.wav', 'fafe8101_nohash_0.wav', '402e2977_nohash_1.wav', '652b3da7_nohash_1.wav', '52162b51_nohash_0.wav', '6565a81d_nohash_0.wav', '87014d40_nohash_0.wav', '10467b06_nohash_0.wav', '1dce06e8_nohash_0.wav', 'ee1d8d49_nohash_0.wav', '62581901_nohash_1.wav', '6021f08b_nohash_1.wav', 'd84829e0_nohash_0.wav', '07363607_nohash_0.wav', 'bd2db1a5_nohash_0.wav', 'c39703ec_nohash_0.wav', '4c13fe25_nohash_0.wav', 'c53b335a_nohash_0.wav', '3c6d55b3_nohash_0.wav', '446a3161_nohash_0.wav', '66a412a7_nohash_0.wav', '4b3a7ad5_nohash_1.wav', 'fbf3dd31_nohash_0.wav', 'ad5aeec2_nohash_0.wav', 'a2b16113_nohash_3.wav', 'ddedba85_nohash_1.wav', '146d97db_nohash_0.wav', '7d149b38_nohash_1.wav', '876c84d6_nohash_1.wav', 'b52bd596_nohash_1.wav', 'e1f1eadc_nohash_0.wav', 'f264e0df_nohash_0.wav', '91cdef62_nohash_1.wav', '51055bda_nohash_0.wav', '989a2213_nohash_0.wav', '56eb74ae_nohash_0.wav', '9b027ecf_nohash_1.wav', 'bdd22e4d_nohash_0.wav', 'b80d6c5e_nohash_1.wav', '9efe5140_nohash_1.wav', '6e916de8_nohash_0.wav', '460f2bad_nohash_0.wav', '5ba724a7_nohash_1.wav', '57cb3575_nohash_0.wav', '6021f08b_nohash_0.wav', '8dc18a75_nohash_0.wav', '30137d34_nohash_0.wav', '845f8553_nohash_0.wav', '71904de3_nohash_0.wav', 'a62f807b_nohash_0.wav', 'd94eb94f_nohash_0.wav', 'e7334395_nohash_2.wav', 'cb802c63_nohash_0.wav', 'ef2a3cfb_nohash_0.wav', 'fe11e258_nohash_0.wav', 'fbf3dd31_nohash_1.wav', 'b0f24c9b_nohash_0.wav', '3efa7ec4_nohash_2.wav', '01b4757a_nohash_1.wav', 'ad6a46f1_nohash_1.wav', 'cab100c9_nohash_0.wav', 'a3502f15_nohash_0.wav', 'db79a764_nohash_0.wav', 'fa446c16_nohash_0.wav', '76e53db9_nohash_0.wav', 'a19452d5_nohash_1.wav', 'cfbedff9_nohash_0.wav', '211b928a_nohash_0.wav', '1365dd89_nohash_1.wav', '7192fddc_nohash_0.wav', 'cd85758f_nohash_0.wav', 'f30285c8_nohash_0.wav', '118261a9_nohash_0.wav', '7e1054e7_nohash_0.wav', 'b87bdb22_nohash_0.wav', '62ff07ef_nohash_1.wav', '0a196374_nohash_0.wav', 'e1469561_nohash_0.wav', '0f7dc557_nohash_0.wav', 'c6ca5d01_nohash_0.wav', 'e11fbc6e_nohash_0.wav', '9fa86a74_nohash_0.wav', 'de650823_nohash_0.wav', '997867e7_nohash_0.wav', 'a8cb6dda_nohash_1.wav', '541e4079_nohash_0.wav', '2b3f509b_nohash_0.wav', '1a5b9ca4_nohash_0.wav', 'a8f45bdc_nohash_1.wav', 'be7fa0a3_nohash_0.wav', '19f9c115_nohash_1.wav', '8d8d9855_nohash_0.wav', 'c692524d_nohash_1.wav', '52bfbce8_nohash_1.wav', 'eb0676ec_nohash_0.wav', 'da76aa58_nohash_1.wav', '5ba724a7_nohash_0.wav', 'c7124b73_nohash_1.wav', 'f2898d06_nohash_0.wav', 'ccea893d_nohash_0.wav', '1942abd7_nohash_0.wav', 'd85270c1_nohash_1.wav', 'ba59cab3_nohash_0.wav', '651d108f_nohash_0.wav', 'd1a4fb3f_nohash_0.wav', '4bc2c2c5_nohash_0.wav', 'ab5ae445_nohash_0.wav', '2c727642_nohash_0.wav', 'c0e0f834_nohash_0.wav', '39a6b995_nohash_0.wav', '305776dd_nohash_1.wav', 'ab46af55_nohash_0.wav', 'd78858d9_nohash_0.wav', 'fffcabd1_nohash_1.wav', '1a9afd33_nohash_1.wav', 'c4e1f6e0_nohash_0.wav', '2be08ce4_nohash_2.wav', 'f5c3de1b_nohash_0.wav', '0d90d8e1_nohash_0.wav', '9acd0254_nohash_0.wav', 'ce49cb60_nohash_0.wav', '462e1919_nohash_0.wav', '821b64cc_nohash_0.wav', 'ea9f8e11_nohash_0.wav', '099d52ad_nohash_0.wav', 'e1aa22e4_nohash_0.wav', 'a3255f5c_nohash_2.wav', '6fb3d5a7_nohash_0.wav', '87c62767_nohash_0.wav', '3209ec42_nohash_0.wav', 'e882abb2_nohash_0.wav', '538e1856_nohash_0.wav', '4340d369_nohash_0.wav', '47d01978_nohash_0.wav', '131e738d_nohash_0.wav', '63ae15e4_nohash_0.wav', 'c0f8f4df_nohash_0.wav', '21832144_nohash_0.wav', '72242187_nohash_0.wav', '270bfa52_nohash_0.wav', '653a48f5_nohash_0.wav', '525eaa62_nohash_0.wav', '18a1aab9_nohash_0.wav', 'f174517e_nohash_0.wav', '3aa6f4e2_nohash_0.wav', '56eab10e_nohash_2.wav', '789e4ee7_nohash_0.wav', '364c0853_nohash_1.wav', '8f3f252c_nohash_0.wav', '19e246ad_nohash_0.wav', '80c45ed6_nohash_1.wav', 'b41a92a3_nohash_0.wav', 'a331d9cb_nohash_0.wav', '9ff2d2f4_nohash_0.wav', '833d9f56_nohash_0.wav', '61e50f62_nohash_0.wav', '5b1db3ee_nohash_4.wav', 'f216055e_nohash_0.wav', 'fd9c7413_nohash_0.wav', '8dd24423_nohash_0.wav', 'c245d3d7_nohash_0.wav', 'd103dd6e_nohash_1.wav', '7dc95912_nohash_1.wav', '312d6d81_nohash_0.wav', '42c6fff1_nohash_1.wav', 'c7aaad67_nohash_0.wav', '234d6a48_nohash_0.wav', '113b3fbc_nohash_0.wav', '2c5e0347_nohash_0.wav', '189cbabe_nohash_0.wav', '2aec99ec_nohash_1.wav', '84999496_nohash_0.wav', '5d9bb361_nohash_1.wav', '09ddc105_nohash_1.wav', '708a9569_nohash_0.wav', '692a88e6_nohash_0.wav', 'ace82a68_nohash_1.wav', '1dc86f91_nohash_0.wav', 'd0858dce_nohash_0.wav', '64df20d8_nohash_0.wav', 'd78858d9_nohash_1.wav', 'c5e3817f_nohash_0.wav', 'f9273a21_nohash_0.wav', '3d794813_nohash_0.wav', '7be5a0f3_nohash_0.wav', 'c578beb0_nohash_0.wav', '1df99a8a_nohash_0.wav', '1b755c65_nohash_1.wav', 'a6285644_nohash_0.wav', '24b82192_nohash_0.wav', '5f47fdf9_nohash_0.wav', '05d18852_nohash_0.wav', '6f342826_nohash_1.wav', '990ebd1f_nohash_1.wav', '409c962a_nohash_2.wav', 'bfb10243_nohash_0.wav', '0e17f595_nohash_0.wav', 'c90c0105_nohash_2.wav', 'b1f8326d_nohash_1.wav', 'da76aa58_nohash_0.wav', 'b8897f1c_nohash_0.wav', '9a76f8c3_nohash_0.wav', '97e0c576_nohash_3.wav', '8c3c4715_nohash_0.wav', 'c0cb43d6_nohash_0.wav', 'e20be42a_nohash_0.wav', '9b8a7439_nohash_0.wav', '9c59dd28_nohash_0.wav', '8ea22de7_nohash_0.wav', '4c594e0f_nohash_0.wav', '472b8045_nohash_0.wav', 'fffcabd1_nohash_0.wav', '014f9f65_nohash_0.wav', 'bde0f20a_nohash_0.wav', '62605293_nohash_0.wav', 'c0c701f1_nohash_0.wav', 'b8874962_nohash_0.wav', 'e9b61425_nohash_1.wav', '31583d30_nohash_0.wav', '1887fe04_nohash_0.wav', '6f342826_nohash_0.wav', '0585b66d_nohash_0.wav', 'fb01a182_nohash_0.wav', 'aff582a1_nohash_0.wav', '61abbf52_nohash_0.wav', 'ab5b211a_nohash_0.wav', 'a04817c2_nohash_0.wav', 'a60a09cf_nohash_0.wav', '57de2379_nohash_1.wav', 'eb6dab4a_nohash_0.wav', '27b9a84f_nohash_0.wav', 'cba7f985_nohash_0.wav', '7b2e879e_nohash_1.wav', '66041c69_nohash_0.wav', '5f8e50a0_nohash_0.wav', 'dae01802_nohash_0.wav', '037c445a_nohash_0.wav', '6d818f6c_nohash_0.wav', 'ece1a95a_nohash_2.wav', '645ed69d_nohash_0.wav', '90645155_nohash_0.wav', 'ea0cf37f_nohash_0.wav', 'fe291fa9_nohash_0.wav', '54ad8f22_nohash_0.wav', 'fb7c9b3b_nohash_2.wav', 'cb72dfb6_nohash_0.wav', '31fd5cf5_nohash_0.wav', 'b76f6088_nohash_0.wav', '97f4c236_nohash_0.wav', 'ede2f4ee_nohash_0.wav', '21cbe292_nohash_0.wav', '6a2fb9a5_nohash_0.wav', '2bd2cad5_nohash_0.wav', '4c13fe25_nohash_2.wav', '91cdef62_nohash_0.wav', 'cf87b736_nohash_0.wav', '2589f361_nohash_0.wav', '1afd49bf_nohash_0.wav', 'ec9b830b_nohash_0.wav', '235b444f_nohash_0.wav', '2aca1e72_nohash_1.wav', '11b1df78_nohash_1.wav', '5828dfa2_nohash_0.wav', 'b66f4f93_nohash_1.wav', '924c1a04_nohash_0.wav', '9c06a3f3_nohash_0.wav', 'cd911ace_nohash_0.wav', 'f34e6f44_nohash_1.wav', '6094340e_nohash_0.wav', '88d009d2_nohash_0.wav', 'a4e8a997_nohash_0.wav', 'a108341b_nohash_0.wav', '8b367d88_nohash_0.wav', '587f3271_nohash_1.wav', 'dcbfe008_nohash_1.wav', 'e71a9381_nohash_0.wav', 'b5d1e505_nohash_1.wav', 'e9b61425_nohash_2.wav', '74b73f88_nohash_0.wav', 'e3411931_nohash_1.wav', '2005ca25_nohash_0.wav', 'e9b61425_nohash_3.wav', '98447c43_nohash_1.wav', '67c7fecb_nohash_0.wav', 'dedc7fab_nohash_0.wav', '042ea76c_nohash_0.wav', 'e7117d00_nohash_0.wav', 'fb7eb481_nohash_0.wav', '3b853f44_nohash_0.wav', 'b00dff7e_nohash_0.wav', '92b2bf59_nohash_0.wav', 'ec989d6d_nohash_0.wav', 'b5935410_nohash_0.wav', '11b1df78_nohash_0.wav', 'a8ee11c7_nohash_0.wav', '951cac20_nohash_1.wav', 'b55a09be_nohash_0.wav', '2aec99ec_nohash_0.wav', '012c8314_nohash_1.wav', '840eab5a_nohash_0.wav', '7c1d8533_nohash_0.wav', '9b027ecf_nohash_0.wav', 'de3fe344_nohash_0.wav', '69953f48_nohash_0.wav', '66774579_nohash_0.wav', 'e91d173e_nohash_0.wav', '772db621_nohash_1.wav', 'd926bb17_nohash_0.wav', '94403ad3_nohash_0.wav', '99fad6a0_nohash_1.wav', '80fe1dc7_nohash_0.wav', '3209ec42_nohash_1.wav', 'aa80f517_nohash_0.wav', 'b1f8326d_nohash_0.wav', '520b2c17_nohash_0.wav', 'ccfd721c_nohash_0.wav', 'c38720cb_nohash_0.wav', '1e9e6bdd_nohash_0.wav', 'a2b16113_nohash_0.wav', 'd486fb84_nohash_1.wav', 'a3255f5c_nohash_1.wav', '4290ca61_nohash_0.wav', 'd7467392_nohash_0.wav', 'af30314d_nohash_0.wav', 'cc3d1613_nohash_0.wav', 'b087aa0e_nohash_0.wav', '837a0f64_nohash_0.wav', '8a28231e_nohash_1.wav', 'ece1a95a_nohash_0.wav', '6f7724f5_nohash_0.wav', '00f0204f_nohash_1.wav', '9331d34b_nohash_0.wav', '508e30ee_nohash_0.wav', '71d0ded4_nohash_0.wav', 'f06190c1_nohash_0.wav', '24ed94ab_nohash_0.wav', '62ef962d_nohash_0.wav', 'ccb1266b_nohash_0.wav', 'fb24c826_nohash_0.wav', '234ab0fb_nohash_0.wav', 'c7dc7278_nohash_0.wav', '4cee0c60_nohash_0.wav', 'c71e3acc_nohash_0.wav', '3eb8764c_nohash_1.wav', 'e2362167_nohash_0.wav', 'c93d5e22_nohash_0.wav', 'c37a72d3_nohash_0.wav', 'a7216980_nohash_0.wav', '14872d06_nohash_1.wav', '8781f4c1_nohash_0.wav', '5f5eef60_nohash_0.wav', '63f7a489_nohash_0.wav', '3102f006_nohash_0.wav', '042186b8_nohash_0.wav', '4bb1244f_nohash_1.wav', '012187a4_nohash_0.wav', 'fb7c9b3b_nohash_1.wav', '1706c35f_nohash_2.wav', '3efa7ec4_nohash_1.wav', '813b82a6_nohash_0.wav', '46114b4e_nohash_2.wav', 'c634a189_nohash_0.wav', '72e382bd_nohash_0.wav', '65ec06e5_nohash_0.wav', 'cf68fad2_nohash_0.wav', '9637f43f_nohash_0.wav', '18c54a68_nohash_4.wav', 'f875f965_nohash_0.wav', '017c4098_nohash_0.wav', '533c6564_nohash_0.wav', '4ca37738_nohash_1.wav', '61482e52_nohash_0.wav', 'f3cee168_nohash_1.wav', '1ecfb537_nohash_0.wav', '7303215d_nohash_0.wav', '4abb2400_nohash_1.wav', '627c0bec_nohash_0.wav', 'e6be0830_nohash_0.wav', '6889b21f_nohash_0.wav', '8f447c3e_nohash_1.wav', '44260689_nohash_0.wav', 'cee22275_nohash_0.wav', 'd6360b32_nohash_0.wav', '617aeb6c_nohash_0.wav', '65d81c54_nohash_0.wav', 'df6bd83f_nohash_0.wav', 'dfdabe19_nohash_1.wav', 'ab46af55_nohash_1.wav', 'e7ea8b76_nohash_1.wav', '3b852f6f_nohash_1.wav', 'f47d644e_nohash_0.wav', '6d7af359_nohash_0.wav', '3411cf4b_nohash_1.wav', '723efc4c_nohash_0.wav', 'c08585c1_nohash_0.wav', '78884794_nohash_1.wav', 'c50225fa_nohash_0.wav', '7c75a504_nohash_0.wav', '9c24bc76_nohash_0.wav', '172dc2b0_nohash_2.wav', 'ee07dcb9_nohash_1.wav', 'c22ebf46_nohash_0.wav', '7081436f_nohash_1.wav', 'bda605da_nohash_0.wav', '2bfe70ef_nohash_0.wav', '2927c601_nohash_0.wav', '4f256313_nohash_0.wav', '65d844fc_nohash_0.wav', '8aa35b0c_nohash_1.wav', 'ef3367d9_nohash_0.wav', '1acc97de_nohash_0.wav', '48a9f771_nohash_1.wav', 'a4e8a997_nohash_1.wav', '09a7aa2a_nohash_0.wav', 'd103dd6e_nohash_0.wav', '8c888bbb_nohash_0.wav', '7303215d_nohash_1.wav', '325a0c39_nohash_0.wav', '3cc595de_nohash_0.wav', '90804775_nohash_0.wav', '6d818f6c_nohash_2.wav', '1a073312_nohash_1.wav', '3b852f6f_nohash_0.wav', '54aecbd5_nohash_0.wav', '6ceeb9aa_nohash_0.wav', '256c0a05_nohash_0.wav', 'c948d727_nohash_0.wav', 'ea7ca285_nohash_1.wav', 'cd8b1781_nohash_0.wav', 'e652590d_nohash_0.wav', 'd4d898d7_nohash_0.wav', '9beccfc8_nohash_0.wav', 'e7334395_nohash_1.wav', '80c17118_nohash_2.wav', 'b5552931_nohash_0.wav', 'b3327675_nohash_1.wav', '9f63152b_nohash_0.wav', '0fc57d61_nohash_0.wav', 'efbb27a6_nohash_0.wav', 'ffd2ba2f_nohash_0.wav', '25c14394_nohash_1.wav', '66aa0f29_nohash_0.wav', '9b5815cd_nohash_2.wav', '229978fd_nohash_0.wav', 'e53139ad_nohash_0.wav', '9b402bc2_nohash_1.wav', 'df5457dc_nohash_0.wav', '94e6864f_nohash_0.wav', 'e269bac0_nohash_1.wav', '82b99576_nohash_0.wav', 'fac7deca_nohash_0.wav', '573cdb8a_nohash_0.wav', '1b63157b_nohash_0.wav', '5236848b_nohash_0.wav', '78102205_nohash_1.wav', '62ccd358_nohash_0.wav', '060cd039_nohash_1.wav', '63996b7c_nohash_0.wav', '43691f67_nohash_0.wav', '5705a0f9_nohash_1.wav', '173ce2be_nohash_1.wav', '66276b0e_nohash_1.wav', 'c392e01d_nohash_0.wav', '1cbcc7a7_nohash_0.wav', '7c83c5f6_nohash_0.wav', '09ddc105_nohash_0.wav', '64220627_nohash_0.wav', 'e6515415_nohash_0.wav', 'c90c0105_nohash_1.wav', '625fd898_nohash_0.wav', 'd9aa8c90_nohash_0.wav', 'cc6ee39b_nohash_0.wav', 'ecef25ba_nohash_0.wav', 'd8a5ace5_nohash_1.wav', 'f34e6f44_nohash_2.wav', 'dce5041a_nohash_1.wav', '244cc3a5_nohash_0.wav', 'c7f9ffb5_nohash_0.wav', '5a0bc987_nohash_0.wav', '333784b7_nohash_0.wav', '6b889021_nohash_2.wav', 'dca2797e_nohash_0.wav', 'd107dc42_nohash_0.wav', 'da2c5f1b_nohash_1.wav', 'a2473d62_nohash_0.wav', 'a05a90c1_nohash_0.wav', 'da2c5f1b_nohash_0.wav', 'b46e8153_nohash_1.wav', '9dc1889e_nohash_0.wav', '5ef35194_nohash_0.wav', '8a0457c9_nohash_1.wav', '3cdecb0b_nohash_1.wav', '479e64cc_nohash_1.wav', '67961766_nohash_0.wav', '97e0c576_nohash_0.wav', '25e95412_nohash_1.wav', 'e7ea8b76_nohash_0.wav', '85d2ac4b_nohash_1.wav', '77def3ee_nohash_0.wav', 'f9643d42_nohash_0.wav', '84d1e469_nohash_1.wav', '333d7ddb_nohash_0.wav', 'a1cff772_nohash_0.wav', '012c8314_nohash_0.wav', '305776dd_nohash_0.wav', '824e8ce5_nohash_0.wav', 'd7a58714_nohash_0.wav', '88d009d2_nohash_1.wav', '50033893_nohash_2.wav', '7257420c_nohash_1.wav', '0c2d2ffa_nohash_1.wav', '8c7f81df_nohash_0.wav', '64574a99_nohash_0.wav', 'e4a2cf79_nohash_0.wav', 'f4f59743_nohash_1.wav', '4c6167ca_nohash_0.wav', '937b433e_nohash_0.wav', 'e855b8f1_nohash_0.wav', '19785c4e_nohash_1.wav', '8a28231e_nohash_0.wav', '5f1b1051_nohash_0.wav', '43f57297_nohash_1.wav', '28460a60_nohash_0.wav', '10627519_nohash_0.wav', '6f342826_nohash_3.wav', '06f6c194_nohash_0.wav', '92a9c5e6_nohash_0.wav', '3a69f765_nohash_0.wav', 'f1eaff75_nohash_1.wav', 'ea7ca285_nohash_0.wav', '067f61e2_nohash_0.wav', '6a203e0e_nohash_1.wav', 'a2473d62_nohash_1.wav', 'f9af823e_nohash_0.wav', '4c841771_nohash_0.wav', '20a0d54b_nohash_0.wav', '65d81c54_nohash_1.wav', '62581901_nohash_0.wav', '682e1687_nohash_1.wav', '0165e0e8_nohash_0.wav', '8f447c3e_nohash_0.wav', '8c4854bc_nohash_0.wav', '902258bb_nohash_0.wav', '0b7ee1a0_nohash_0.wav', 'f19d1738_nohash_0.wav', 'f68160c0_nohash_0.wav', 'fa70c187_nohash_0.wav', 'bf70feda_nohash_0.wav', '1ed557b9_nohash_0.wav', 'bda605da_nohash_1.wav', '65c73b55_nohash_0.wav', 'c099668c_nohash_3.wav', '3ce4910e_nohash_0.wav', '881583a6_nohash_0.wav', '0b09edd3_nohash_0.wav', '18c54a68_nohash_0.wav', '815f0f03_nohash_0.wav', 'ae82c78c_nohash_0.wav', 'd57febf0_nohash_0.wav', 'fa44fcf5_nohash_0.wav', '8b775397_nohash_1.wav', '5677ec77_nohash_0.wav', '772db621_nohash_0.wav', '3e3b65eb_nohash_0.wav', '37b03ab1_nohash_0.wav', 'e82914c0_nohash_0.wav', 'da7689f1_nohash_1.wav', '563aa4e6_nohash_0.wav', 'e10e2cbb_nohash_0.wav', '418e7158_nohash_0.wav', '13199b79_nohash_0.wav', 'f5e5e8b0_nohash_1.wav', 'f822b9bf_nohash_0.wav', 'b43de700_nohash_0.wav', 'e4b02540_nohash_1.wav', '650daf8e_nohash_1.wav', '94e6864f_nohash_1.wav', '71f6fed7_nohash_0.wav', 'b4604db4_nohash_0.wav', '60472d26_nohash_1.wav', '5efb758c_nohash_0.wav', 'e3411931_nohash_0.wav', '78030270_nohash_0.wav', 'ece1a95a_nohash_1.wav', '83c9e7e6_nohash_1.wav', '8fe67225_nohash_0.wav', 'a8cf01bc_nohash_1.wav', '62ef962d_nohash_1.wav', 'd1d3e64d_nohash_0.wav', '8d8d9855_nohash_2.wav', 'd8521ea0_nohash_1.wav', '9190045a_nohash_0.wav', '5fadb538_nohash_0.wav', '1df483c0_nohash_0.wav', 'f59d0771_nohash_0.wav', 'cee22275_nohash_1.wav', '3ab9ba07_nohash_0.wav', '0474c92a_nohash_1.wav', 'a9abc695_nohash_1.wav', 'f736ab63_nohash_0.wav', '1365dd89_nohash_0.wav', 'b3849d6e_nohash_0.wav', 'c2d74084_nohash_0.wav', 'a24cf51c_nohash_1.wav', 'f104f742_nohash_2.wav', '30065f33_nohash_1.wav', 'b0f5b16d_nohash_0.wav', 'c0445658_nohash_0.wav', 'a1a59b72_nohash_0.wav', '876c84d6_nohash_0.wav', '1e4064b8_nohash_0.wav', 'd9b50b8b_nohash_0.wav', '0137b3f4_nohash_0.wav', 'b71ebf79_nohash_0.wav', 'b12bef84_nohash_1.wav', '34263ab3_nohash_0.wav', '6347b393_nohash_2.wav', '1a994c9f_nohash_0.wav', 'b1426003_nohash_0.wav', '1a6eca98_nohash_0.wav', '863880b7_nohash_0.wav', '18d84076_nohash_0.wav', '1ed0b13d_nohash_0.wav', 'b0c0197e_nohash_0.wav', 'f5626af6_nohash_0.wav', '6a1908f8_nohash_0.wav', '99e6cab8_nohash_0.wav', '5a5721f8_nohash_0.wav', '4beff0c5_nohash_2.wav', 'c4500713_nohash_0.wav', '27c24504_nohash_0.wav', '93ec8b84_nohash_1.wav', 'd85270c1_nohash_0.wav', '7dc95912_nohash_0.wav', 'b1114e4f_nohash_0.wav', '6205088b_nohash_3.wav', '3bfd30e6_nohash_0.wav', 'bca56796_nohash_0.wav', 'f804cbb3_nohash_0.wav', '6a700f9d_nohash_0.wav', '96a48d28_nohash_0.wav', '016e2c6d_nohash_0.wav', 'e3e0f145_nohash_0.wav', '91cdef62_nohash_2.wav', '78622c2b_nohash_0.wav', 'afb9e62e_nohash_1.wav', 'b29f8b23_nohash_0.wav', '479e64cc_nohash_0.wav', '409c962a_nohash_0.wav', 'b2fbe484_nohash_0.wav', '42ccb57a_nohash_0.wav', '48463cbc_nohash_2.wav', '95299b6c_nohash_0.wav', '1a6eca98_nohash_1.wav', '7d5f87c8_nohash_0.wav', '9587481f_nohash_0.wav', '9886d8bf_nohash_0.wav', '46114b4e_nohash_1.wav', '6366f61a_nohash_0.wav', 'e900b652_nohash_0.wav', 'f174517e_nohash_1.wav', '353b4d33_nohash_0.wav', '8ea6dec6_nohash_1.wav', 'f9bdf10e_nohash_1.wav', 'fa7895de_nohash_0.wav', '3389305e_nohash_0.wav', '6cc28ce5_nohash_0.wav', 'bed06fac_nohash_2.wav', '73f0c1f7_nohash_0.wav', 'a527cb3c_nohash_0.wav', 'cc592808_nohash_1.wav', 'e9abfe31_nohash_0.wav', '8335f893_nohash_0.wav', '97ae8b25_nohash_1.wav', '9e42ae25_nohash_0.wav', '2bd2cad5_nohash_1.wav', '30060aba_nohash_0.wav', 'ec32860c_nohash_0.wav', 'd3831f6a_nohash_0.wav', '265bd13a_nohash_0.wav', '6f5b4d3d_nohash_2.wav', '5a9f7324_nohash_0.wav', '5f8e50a0_nohash_1.wav', 'ead2934a_nohash_0.wav', 'ab7b5acd_nohash_0.wav', 'ffb86d3c_nohash_0.wav', 'c0c701f1_nohash_1.wav', 'b843de62_nohash_0.wav', '20fd451f_nohash_0.wav', 'bdb90d38_nohash_1.wav', '81dc4a94_nohash_0.wav', 'd278d8ef_nohash_0.wav', 'cb2929ce_nohash_0.wav', 'fa52ddf6_nohash_0.wav', 'f4386675_nohash_0.wav', '493392c6_nohash_1.wav', '82c6d220_nohash_0.wav', '23abe1c9_nohash_0.wav', '4f086393_nohash_1.wav', 'd21fd169_nohash_0.wav', '0d2bcf9d_nohash_1.wav', '4407ba92_nohash_0.wav', '7fa5fa1f_nohash_0.wav', 'baf01c1f_nohash_0.wav', '079dfce3_nohash_1.wav', '8d8d9855_nohash_1.wav', 'dd6c6806_nohash_0.wav', '42e3f068_nohash_0.wav', '28612180_nohash_2.wav', '8a0457c9_nohash_0.wav', '8442ea62_nohash_0.wav', '989a2213_nohash_1.wav', '32ad5b65_nohash_0.wav', '17f0e206_nohash_1.wav', 'caa7feaf_nohash_0.wav', 'b5d1e505_nohash_0.wav', '0c40e715_nohash_0.wav', 'a50a98d2_nohash_0.wav', '89d6d11e_nohash_0.wav', '9e6bb505_nohash_1.wav', '1e02ffc5_nohash_0.wav', 'f00180d0_nohash_0.wav', '493392c6_nohash_0.wav', '1cb788bc_nohash_1.wav', '0135f3f2_nohash_0.wav', '004ae714_nohash_0.wav', '3a789a0d_nohash_0.wav', 'a16b3102_nohash_0.wav', '1a073312_nohash_0.wav', '262d7a03_nohash_0.wav', '9712cce0_nohash_0.wav', '92b2bf59_nohash_2.wav', '7c9b43f0_nohash_0.wav', '2fee065a_nohash_0.wav', '370844f7_nohash_0.wav', '6f5b4d3d_nohash_1.wav', '7add4c5f_nohash_0.wav', '89f680f3_nohash_0.wav', 'd53e25ba_nohash_1.wav', 'd2f4f431_nohash_2.wav', 'f852895b_nohash_0.wav', 'fb7c9b3b_nohash_0.wav', '25040e85_nohash_0.wav', '31583d30_nohash_1.wav', '063d48cf_nohash_0.wav', 'a929f9b9_nohash_0.wav', 'eb67fcbc_nohash_0.wav', 'c692524d_nohash_0.wav', '01648c51_nohash_1.wav', '73124b26_nohash_0.wav', '48463cbc_nohash_1.wav', '57de2379_nohash_0.wav', '47565088_nohash_1.wav', 'ce9410da_nohash_1.wav', '37e8db82_nohash_0.wav', '988e2f9a_nohash_0.wav', 'b93528e3_nohash_0.wav', 'f4cae173_nohash_0.wav', '28ef2a01_nohash_0.wav', '5b09db89_nohash_0.wav', '708a9569_nohash_1.wav', '8a744054_nohash_0.wav', 'fad7a69a_nohash_0.wav', '10ace7eb_nohash_0.wav', 'ae927455_nohash_0.wav', '1a673010_nohash_0.wav', 'ac9dee0e_nohash_0.wav', '1a5b9ca4_nohash_1.wav', '5e033479_nohash_0.wav', '11a022ba_nohash_0.wav', 'b43c8f2f_nohash_1.wav', '825f450d_nohash_1.wav', '44c201dd_nohash_0.wav', '1890e5c3_nohash_0.wav', '6b889021_nohash_0.wav', 'caa4779f_nohash_0.wav', 'bc065a17_nohash_1.wav', '4b25f620_nohash_0.wav', 'b1df80c0_nohash_1.wav', '94e6864f_nohash_3.wav', 'a24582a0_nohash_1.wav', 'b487da60_nohash_0.wav', '173ae793_nohash_1.wav', '66cff190_nohash_1.wav', '1473be6a_nohash_0.wav', 'f2a90886_nohash_0.wav', '7eee5973_nohash_1.wav', '77f185d3_nohash_1.wav', '83f9c4ab_nohash_0.wav', 'ac7840d8_nohash_0.wav', '0bde966a_nohash_0.wav', 'ca6d5cd1_nohash_0.wav', '215699ff_nohash_0.wav', '8281a2a8_nohash_0.wav', 'c71e3acc_nohash_1.wav', '305776dd_nohash_2.wav', '28497c5b_nohash_0.wav', '716757ce_nohash_1.wav', '587f3271_nohash_0.wav', 'f9bdf10e_nohash_0.wav', 'b15fc37d_nohash_0.wav', '4c7c95de_nohash_1.wav', 'dcc012ec_nohash_1.wav', 'e4a2cf79_nohash_1.wav', '26e573a9_nohash_0.wav', 'e95c70e2_nohash_0.wav', '60472d26_nohash_2.wav', 'b49caed3_nohash_0.wav', 'e41a903b_nohash_0.wav', '97ae8b25_nohash_0.wav', '07c5129e_nohash_0.wav', 'b46e8153_nohash_0.wav', '4a803e67_nohash_1.wav', 'b5cf6ea8_nohash_1.wav', '460209ac_nohash_0.wav', '0ea0e2f4_nohash_0.wav', 'ba676390_nohash_0.wav', 'c7124b73_nohash_2.wav', '8ea6dec6_nohash_0.wav', 'b0f24c9b_nohash_1.wav', 'ad89eb1e_nohash_0.wav', 'b41a92a3_nohash_1.wav', 'f88f97a7_nohash_0.wav', 'd5b963aa_nohash_0.wav', '1c3f50ad_nohash_0.wav', '5b1db3ee_nohash_1.wav', '9ff1b8b6_nohash_0.wav', '413997c1_nohash_0.wav', '3c8dc702_nohash_0.wav', 'eb3f7d82_nohash_0.wav', '48e8b82a_nohash_0.wav', 'c2bc4489_nohash_0.wav', 'd3f22f0e_nohash_0.wav', 'a5d485dc_nohash_0.wav', '55d3725a_nohash_0.wav', '0a7c2a8d_nohash_0.wav', '5ff3f9a1_nohash_0.wav', '65040d9b_nohash_0.wav', '50033893_nohash_0.wav', '00176480_nohash_0.wav', '8353fea1_nohash_0.wav', '6166ae21_nohash_0.wav', '89f680f3_nohash_1.wav', '8ec6dab6_nohash_1.wav', 'e3e49931_nohash_2.wav', 'db7c95b0_nohash_0.wav', '85d2ac4b_nohash_0.wav', '01b4757a_nohash_0.wav', '650daf8e_nohash_2.wav', '3ef0f3ab_nohash_0.wav', 'facd97c0_nohash_0.wav', '88a487ce_nohash_0.wav', '7213ed54_nohash_0.wav', 'a84dee7b_nohash_0.wav', 'c50f55b8_nohash_3.wav', 'cc3d1613_nohash_2.wav', '6c0f6493_nohash_0.wav', 'e48a80ed_nohash_0.wav', 'a2b16113_nohash_1.wav', 'f9af823e_nohash_1.wav', '87070229_nohash_0.wav', '1993db46_nohash_0.wav', '96c67073_nohash_0.wav', '5769c5ab_nohash_0.wav', '650daf8e_nohash_0.wav', 'ca4912b6_nohash_0.wav', 'b97c9f77_nohash_0.wav', 'bc999754_nohash_0.wav', '87d5e978_nohash_0.wav', '3ed3e49a_nohash_2.wav', 'e76dd1ce_nohash_0.wav', '7dc50b88_nohash_0.wav', '171edea9_nohash_0.wav', '82e7204d_nohash_0.wav', '518588b6_nohash_2.wav', '879a2b38_nohash_0.wav', '92b2bf59_nohash_1.wav', '31d31fa0_nohash_0.wav', '6ace4fe1_nohash_0.wav', '39dce8cc_nohash_0.wav', 'e6be0830_nohash_1.wav', 'afabfa0e_nohash_0.wav', '0c2ca723_nohash_1.wav', 'dcc012ec_nohash_0.wav', '8aa35b0c_nohash_0.wav', '4beff0c5_nohash_1.wav', '42e3f068_nohash_1.wav', '4b25f620_nohash_1.wav', '42c6fff1_nohash_0.wav', 'ee07dcb9_nohash_2.wav', '51c5601d_nohash_0.wav', 'b00c4c53_nohash_0.wav', '86648261_nohash_1.wav', '3d9bbe2d_nohash_0.wav', 'd3f22f0e_nohash_2.wav', '9a7c1f83_nohash_0.wav', 'c08e5058_nohash_0.wav', '05739450_nohash_0.wav', 'bf90a57a_nohash_0.wav', 'caa7feaf_nohash_1.wav', 'fbe51750_nohash_1.wav', '5b32733e_nohash_0.wav', 'bbd0bbd0_nohash_0.wav', '61d3e51e_nohash_0.wav', 'a19452d5_nohash_0.wav', '61bcb275_nohash_0.wav', '25c14394_nohash_0.wav', '409c962a_nohash_1.wav', 'c781f251_nohash_0.wav', '48a9f771_nohash_0.wav', '1a892463_nohash_0.wav', '173ae793_nohash_0.wav', 'eeaf97c3_nohash_0.wav', '531a5b8a_nohash_0.wav', 'f7b43563_nohash_0.wav', 'b3bdded5_nohash_0.wav', 'e10e2cbb_nohash_1.wav', '7a5530c9_nohash_1.wav', '0b77ee66_nohash_2.wav', 'f2e59fea_nohash_0.wav', 'e20be42a_nohash_1.wav', 'c25a032b_nohash_0.wav', '2e8c59f7_nohash_0.wav', '00f0204f_nohash_0.wav', '89f3ab7d_nohash_1.wav', 'cc3d1613_nohash_1.wav', 'dc2222d7_nohash_1.wav', 'be7a5b2d_nohash_0.wav', 'ce49cb60_nohash_1.wav', 'c678e0b3_nohash_0.wav', '6d818f6c_nohash_1.wav', '43b85b64_nohash_0.wav', '17f0e206_nohash_0.wav', 'f0ae7203_nohash_0.wav', 'a518d1cf_nohash_0.wav', '70a00e98_nohash_0.wav', '8eb4a1bf_nohash_0.wav', 'aa48c94a_nohash_1.wav', 'e9901cf0_nohash_0.wav', '99081f4d_nohash_0.wav', '422d3197_nohash_0.wav', '50a7d406_nohash_0.wav', '27b03931_nohash_0.wav', 'd53e25ba_nohash_0.wav', '435f9f9e_nohash_0.wav', 'cf8d91cf_nohash_0.wav', 'e3e49931_nohash_1.wav', 'c4cfbe43_nohash_0.wav', 'fb727898_nohash_0.wav', 'd8c52371_nohash_0.wav', '21e8c417_nohash_0.wav', '513aeddf_nohash_0.wav', '750e3e75_nohash_0.wav', '5828dfa2_nohash_1.wav', 'f575faf3_nohash_0.wav', 'e3e49931_nohash_0.wav', '97e0c576_nohash_1.wav', '3de53d23_nohash_0.wav', 'f5733968_nohash_0.wav', 'dec73123_nohash_0.wav', 'b3bb4dd6_nohash_1.wav', '4b3a7ad5_nohash_0.wav', '64a80906_nohash_1.wav', '09bcdc9d_nohash_1.wav', '9b5815cd_nohash_0.wav', 'fc94edb0_nohash_1.wav', 'd2f4f431_nohash_1.wav', '39afb88e_nohash_0.wav', '16db1582_nohash_0.wav', '18a8f03f_nohash_2.wav', '765ffccb_nohash_1.wav', 'b83c1acf_nohash_0.wav', '3df9a3d4_nohash_0.wav', '92e17cc4_nohash_1.wav', '8f3f252c_nohash_2.wav', '23da904f_nohash_0.wav', '34e8c726_nohash_0.wav', '72320401_nohash_0.wav', '54412eae_nohash_0.wav', '19f9c115_nohash_0.wav', 'fbb2f6cc_nohash_0.wav', '89f3ab7d_nohash_0.wav', '0474c92a_nohash_0.wav', '6347b393_nohash_0.wav', '1b4c9b89_nohash_0.wav', '611d2b50_nohash_0.wav', '2f0ce4d9_nohash_0.wav', 'd6b155a5_nohash_0.wav', '1aed7c6d_nohash_0.wav', 'c1d39ce8_nohash_0.wav', '12529547_nohash_0.wav', '5f9cd2eb_nohash_1.wav', '2a0b413e_nohash_0.wav', '8b367d88_nohash_2.wav', '2796ac50_nohash_0.wav', '919d3c0e_nohash_0.wav', '24ed94ab_nohash_1.wav', '13dce503_nohash_0.wav', '1970b130_nohash_0.wav', 'd31d8dd7_nohash_0.wav', '70880cc6_nohash_0.wav', 'adc216c5_nohash_0.wav', '73f20b00_nohash_0.wav', '14c7b073_nohash_0.wav', '5a98d407_nohash_0.wav', '30065f33_nohash_0.wav', '0e17f595_nohash_1.wav', 'f6617a86_nohash_0.wav', '982babaf_nohash_0.wav', '40738a2d_nohash_0.wav', '87eff300_nohash_0.wav', 'b7a6f709_nohash_1.wav', '7799c9cd_nohash_1.wav', '102192fd_nohash_0.wav', '462e1919_nohash_1.wav', 'b9f46737_nohash_0.wav', 'af54ec46_nohash_0.wav', '712e4d58_nohash_0.wav', 'f5e5e8b0_nohash_2.wav', '61a9f72a_nohash_0.wav', 'f6af2457_nohash_0.wav', '590750e8_nohash_1.wav', '37dca74f_nohash_0.wav', 'efa16ffd_nohash_0.wav', 'e8c3c5ca_nohash_0.wav', '1a4259c3_nohash_0.wav', '4abb2400_nohash_0.wav', '3837f3f3_nohash_0.wav', '30f31e42_nohash_0.wav', 'b26343e9_nohash_0.wav', 'f9318c93_nohash_0.wav', 'c9a5100f_nohash_0.wav', '3eb8764c_nohash_0.wav', '23ad12d8_nohash_0.wav', '197f4153_nohash_0.wav', '962f27eb_nohash_0.wav', '86402da1_nohash_0.wav', 'c256377f_nohash_0.wav', '990ebd1f_nohash_0.wav', '26a093e1_nohash_0.wav', '551e42e8_nohash_0.wav', 'a1c63f25_nohash_0.wav', '951cac20_nohash_0.wav', 'aa753bb9_nohash_0.wav', '43fc47a7_nohash_0.wav', '5b1db3ee_nohash_0.wav', '587f3271_nohash_2.wav', '2313e093_nohash_0.wav', 'f104f742_nohash_1.wav', '4fd1443e_nohash_0.wav', '34263ab3_nohash_1.wav', '7910d292_nohash_0.wav', 'bf5d409d_nohash_0.wav', '8c7c9168_nohash_0.wav', '825f450d_nohash_2.wav', '50f55535_nohash_0.wav', '89ed36ab_nohash_0.wav', '30276d03_nohash_0.wav', '69086eb0_nohash_0.wav', 'adebe223_nohash_0.wav', 'cce17a61_nohash_1.wav', '0717b9f6_nohash_0.wav', '44e9d8d2_nohash_0.wav', 'c256377f_nohash_1.wav', '9a2e5b3c_nohash_0.wav', '0ea0e2f4_nohash_1.wav', '559bc36a_nohash_0.wav', 'ae04cdbe_nohash_0.wav', 'b4aa9fef_nohash_0.wav', 'f7b43563_nohash_1.wav', 'b06c19b0_nohash_0.wav', 'e5d2e09d_nohash_1.wav', '7799c9cd_nohash_0.wav', 'cc3b5b62_nohash_0.wav', '7b2e879e_nohash_0.wav', '6aa8def4_nohash_0.wav', 'da040491_nohash_0.wav', '8bbd98d0_nohash_0.wav', '591d32f3_nohash_1.wav', '18c54a68_nohash_2.wav', '1b42b551_nohash_0.wav', '531a5b8a_nohash_1.wav', '1d1fe0a0_nohash_0.wav', 'c9b653a0_nohash_0.wav', '3d86b69a_nohash_0.wav', '3291330e_nohash_0.wav', '6b889021_nohash_1.wav', 'fe1916ba_nohash_0.wav', '3efa7ec4_nohash_0.wav', 'ed032775_nohash_0.wav', 'b5cf6ea8_nohash_0.wav', '964c7c9e_nohash_0.wav', 'ab5ae445_nohash_1.wav', '0132a06d_nohash_0.wav', 'ab71c9a7_nohash_0.wav', 'ace072ba_nohash_0.wav', '863880b7_nohash_1.wav', '31270cb2_nohash_1.wav', '4e61bf96_nohash_0.wav', '3bc21161_nohash_0.wav', '4cb874bb_nohash_0.wav', '6414258b_nohash_0.wav', '18f8afd5_nohash_0.wav', 'e77d88fc_nohash_0.wav', '9a356ab9_nohash_0.wav', '16d41d07_nohash_0.wav', '0d393936_nohash_0.wav', 'c50f55b8_nohash_0.wav', 'b43c8f2f_nohash_0.wav', 'a4baac4e_nohash_1.wav', 'c2aeb59d_nohash_0.wav', '617de221_nohash_0.wav', 'bc065a17_nohash_2.wav', '619b5164_nohash_1.wav', 'f84762e5_nohash_0.wav', 'e71b4ce6_nohash_0.wav', '62ccd358_nohash_1.wav', '1473be6a_nohash_1.wav', '2c727642_nohash_2.wav', 'cce17a61_nohash_2.wav', '7211390b_nohash_0.wav', '682e1687_nohash_0.wav', '88e90bc1_nohash_0.wav', '9b402bc2_nohash_0.wav', 'ce49cb60_nohash_2.wav', 'da584bc0_nohash_0.wav', 'bd8412df_nohash_0.wav', 'da5dadb9_nohash_0.wav', '605ed0ff_nohash_0.wav', '9be15e93_nohash_0.wav', '9448c397_nohash_0.wav', '499be02e_nohash_0.wav', '6f5b4d3d_nohash_3.wav', 'c518d1b1_nohash_0.wav', '5170b77f_nohash_0.wav', '004ae714_nohash_1.wav', 'ec545975_nohash_2.wav', 'a8cb6dda_nohash_0.wav', 'd952a17e_nohash_0.wav', 'c4e00ee9_nohash_0.wav', 'dac8b7f9_nohash_0.wav', 'ce9410da_nohash_0.wav', '529eda42_nohash_0.wav', '66cff190_nohash_2.wav', '88120683_nohash_0.wav', 'a902ce9b_nohash_0.wav', '413bcfe1_nohash_0.wav', 'c50f55b8_nohash_5.wav', 'f104f742_nohash_0.wav', '80c45ed6_nohash_0.wav', 'b0c0197e_nohash_1.wav', 'ab81c9c8_nohash_0.wav', 'da8fa823_nohash_0.wav', '7ff085e1_nohash_0.wav', '402e2977_nohash_0.wav', 'e72aa705_nohash_1.wav', '1706c35f_nohash_3.wav', 'b6ebe225_nohash_1.wav', 'cc592808_nohash_0.wav', '620ff0fa_nohash_0.wav', '0362539c_nohash_1.wav', '91b03183_nohash_0.wav', '30802c5d_nohash_0.wav', '6c968bd9_nohash_0.wav', '1ffd513b_nohash_0.wav', 'f19279c4_nohash_0.wav', 'bb31b82b_nohash_0.wav', '19785c4e_nohash_2.wav', 'b6091c84_nohash_1.wav', 'e5afa9b0_nohash_0.wav', '1efdf53f_nohash_0.wav', '44bc77f7_nohash_0.wav', '77f185d3_nohash_0.wav', '62b7c848_nohash_0.wav', '94e6864f_nohash_4.wav', '652b3da7_nohash_2.wav', 'b52bd596_nohash_0.wav', '6823565f_nohash_0.wav', 'e805a617_nohash_0.wav', '35c8fa78_nohash_0.wav', '32efce64_nohash_0.wav', '9db2bfe9_nohash_0.wav', 'd5ca80c6_nohash_0.wav', '86648261_nohash_0.wav', '105e72bb_nohash_0.wav', '28612180_nohash_0.wav', '67961766_nohash_1.wav', '773e26f7_nohash_0.wav', 'a996cf66_nohash_0.wav', 'ede2f4ee_nohash_1.wav', '8e05039f_nohash_0.wav', 'f638a812_nohash_1.wav', '553f1a79_nohash_0.wav', 'e5d2e09d_nohash_0.wav', '5e3dde6b_nohash_0.wav', 'ec545975_nohash_3.wav', 'ee28caac_nohash_0.wav', 'dcbfe008_nohash_0.wav', '57152045_nohash_1.wav', '0c2d2ffa_nohash_0.wav', '9d4bab4f_nohash_0.wav', '4def68db_nohash_1.wav', '19f9c115_nohash_3.wav', '02746d24_nohash_0.wav', 'efc5e569_nohash_0.wav', 'cc4f9250_nohash_0.wav', '41474817_nohash_0.wav', '60472d26_nohash_0.wav', '14872d06_nohash_0.wav', '0d2bcf9d_nohash_0.wav', '47565088_nohash_0.wav', 'c842b5e4_nohash_1.wav', 'ec201020_nohash_0.wav', 'c351e611_nohash_0.wav', '77def3ee_nohash_1.wav', '6b7d5101_nohash_0.wav', '1bb574f9_nohash_0.wav', '079dfce3_nohash_2.wav', 'c2657ba5_nohash_1.wav', 'c0cb43d6_nohash_1.wav', '0bde966a_nohash_1.wav', '6205088b_nohash_1.wav', 'adebe223_nohash_1.wav', 'cd8b1781_nohash_1.wav', 'e55a2b20_nohash_1.wav', 'fd9c7413_nohash_1.wav', '29dce108_nohash_0.wav', 'aa48c94a_nohash_0.wav', 'b21f0fa4_nohash_0.wav', '265bd13a_nohash_1.wav', '54d9ccb5_nohash_0.wav', 'c68cf200_nohash_0.wav', '54b6d355_nohash_0.wav', 'c1e0e8e3_nohash_0.wav', 'e5e54cee_nohash_0.wav', 'd0ce2418_nohash_0.wav', '964e8cfd_nohash_0.wav', '7f208e83_nohash_0.wav', '105a0eea_nohash_0.wav', 'cc71bada_nohash_1.wav', '541120c7_nohash_0.wav', '7a5530c9_nohash_0.wav', '9e2ce5e3_nohash_0.wav', '7f208e83_nohash_1.wav', '86f12ac0_nohash_0.wav', '25e95412_nohash_0.wav', 'dfdabe19_nohash_0.wav', 'eb67fcbc_nohash_1.wav', 'ab353673_nohash_0.wav', '264f471d_nohash_0.wav', 'dd6c6806_nohash_1.wav', '6071a214_nohash_0.wav', '7e7ca854_nohash_0.wav', '1bb6ed89_nohash_1.wav', 'b26343e9_nohash_2.wav', '4e61bf96_nohash_2.wav', 'af6fbbf5_nohash_0.wav', '518588b6_nohash_0.wav', 'ff0e27c3_nohash_0.wav', 'f9af0887_nohash_1.wav', 'c842b5e4_nohash_0.wav', '238c112c_nohash_0.wav', '2b5e346d_nohash_0.wav', 'dabf67d9_nohash_0.wav', '95218ce8_nohash_0.wav', 'b3bb4dd6_nohash_0.wav', '69a1a79f_nohash_0.wav', '8c3c4715_nohash_1.wav', '3e31dffe_nohash_0.wav', 'cc554de3_nohash_0.wav', '7eee5973_nohash_0.wav', 'f21893dc_nohash_1.wav', '78102205_nohash_0.wav', 'b3bdded5_nohash_1.wav', '3b3d2f59_nohash_0.wav', 'caa4779f_nohash_1.wav', '627c0bec_nohash_1.wav', '34ba417a_nohash_0.wav', 'db7c95b0_nohash_2.wav', '1a0f9c63_nohash_0.wav', 'cce17a61_nohash_0.wav', '5a3712c9_nohash_0.wav', '5677ec77_nohash_1.wav', 'f4504600_nohash_1.wav', '060cd039_nohash_0.wav', 'dbb7723a_nohash_0.wav', '1a4259c3_nohash_1.wav', '0b77ee66_nohash_1.wav', '47565088_nohash_2.wav', '578d3efb_nohash_0.wav', '679463fc_nohash_0.wav', 'cc71bada_nohash_0.wav', 'f35eedd7_nohash_0.wav', '7ea032f3_nohash_0.wav', '3e3fa7fd_nohash_0.wav', '0447d7c1_nohash_0.wav', '9a69672b_nohash_0.wav', 'd9b8fab2_nohash_0.wav', 'e9b61425_nohash_0.wav', 'c33682f0_nohash_0.wav', '2e75d37a_nohash_0.wav', '988e2f9a_nohash_1.wav', '619b5164_nohash_0.wav', 'e20be42a_nohash_2.wav', '81332c92_nohash_0.wav', '20174140_nohash_0.wav', '7fc74fbe_nohash_0.wav', '6ceeb9aa_nohash_1.wav', '311fde72_nohash_0.wav', 'b3327675_nohash_0.wav', 'b0ae6326_nohash_0.wav', 'b0bad4a9_nohash_0.wav', '4fce7686_nohash_1.wav', '079dfce3_nohash_0.wav', '50a8ef27_nohash_0.wav', '17c94b23_nohash_0.wav', 'cb802c63_nohash_1.wav', 'd8ee4734_nohash_0.wav', '0cb74144_nohash_0.wav', '5ebc1cda_nohash_0.wav', '63996b7c_nohash_1.wav', 'c7e02d9c_nohash_0.wav', '826268f8_nohash_0.wav', 'a8cf01bc_nohash_0.wav', '2d82a556_nohash_0.wav', '7846fd85_nohash_0.wav', '726382d6_nohash_0.wav', '2005ca25_nohash_1.wav', '28e47b1a_nohash_0.wav', 'c099668c_nohash_2.wav', 'b91b718c_nohash_0.wav', '981e2a16_nohash_1.wav', 'd0745d72_nohash_0.wav', 'e8c3c5ca_nohash_1.wav', 'a331d9cb_nohash_2.wav', 'ce7a8e92_nohash_0.wav', '01648c51_nohash_0.wav', '4c432947_nohash_2.wav', '5c8af87a_nohash_0.wav', '7e4fa1d8_nohash_0.wav', '2a89ad5c_nohash_0.wav', 'd3c2470e_nohash_0.wav', 'bed06fac_nohash_1.wav', '6a203e0e_nohash_0.wav', '5fb88f4c_nohash_0.wav', '68dd409e_nohash_0.wav', 'ddedba85_nohash_2.wav', '62605293_nohash_1.wav', 'b7016c27_nohash_0.wav', '9d8ac38b_nohash_0.wav', '742d6431_nohash_0.wav', '19785c4e_nohash_0.wav', '0d6d7360_nohash_0.wav', '83c9e7e6_nohash_0.wav', '5f9cd2eb_nohash_0.wav', 'ead2934a_nohash_2.wav', '6a014b29_nohash_0.wav', '1a9afd33_nohash_0.wav', '4845bb10_nohash_0.wav', '18e910f4_nohash_0.wav', 'c50225fa_nohash_1.wav', '8f3f252c_nohash_1.wav', 'c90c0105_nohash_0.wav', 'b66f4f93_nohash_0.wav', 'da7689f1_nohash_0.wav', '98447c43_nohash_0.wav', 'd2f4f431_nohash_0.wav', '8d5d076d_nohash_0.wav', '78884794_nohash_0.wav', '57152045_nohash_0.wav', '6bf5baf3_nohash_0.wav', '0f46028a_nohash_0.wav', '4f8ef132_nohash_0.wav', '3cfc6b3a_nohash_0.wav', '638548d5_nohash_0.wav', 'e54a0f16_nohash_0.wav', 'f3cee168_nohash_0.wav', 'a1e71565_nohash_0.wav', '339f2c5c_nohash_0.wav', 'dfdabe19_nohash_2.wav', 'efa16ffd_nohash_1.wav', '3d6bee47_nohash_0.wav', 'dd086776_nohash_0.wav', '90b0b91a_nohash_0.wav', '981e2a16_nohash_0.wav', '92e17cc4_nohash_0.wav', '300384f0_nohash_1.wav', '2748cce7_nohash_0.wav', 'ee07dcb9_nohash_0.wav', 'eb6dab4a_nohash_1.wav', 'bc065a17_nohash_0.wav', 'e0ff1e9c_nohash_0.wav', 'ec7d1151_nohash_0.wav', '88b7c5fa_nohash_0.wav', 'ea356919_nohash_0.wav', 'f4cae173_nohash_1.wav', 'bb05582b_nohash_0.wav', '96c67073_nohash_1.wav', 'acfd3bc3_nohash_0.wav', '2c6446f7_nohash_0.wav', '9a4d12fd_nohash_0.wav', '15c371c7_nohash_0.wav', 'ab00c4b2_nohash_0.wav', '6c429c7b_nohash_0.wav', 'c50f55b8_nohash_2.wav', '6e41a77e_nohash_0.wav', '1657c9fa_nohash_0.wav', 'a7dd45cf_nohash_0.wav', '57b68383_nohash_0.wav', 'b80d6c5e_nohash_0.wav', 'd1dd03ed_nohash_0.wav', '300384f0_nohash_0.wav', '902258bb_nohash_1.wav', 'f44f440f_nohash_0.wav', 'e8d562ca_nohash_0.wav', '848e7f6e_nohash_0.wav', '68effe85_nohash_0.wav', 'b55a09be_nohash_1.wav', '2510c044_nohash_0.wav', 'f632210f_nohash_0.wav', '28612180_nohash_1.wav', '81898f68_nohash_0.wav', 'c0fb6812_nohash_1.wav', 'ff2b842e_nohash_0.wav', 'cfde27ba_nohash_0.wav', '9a4d12fd_nohash_1.wav', 'ef77b778_nohash_0.wav', 'c245d3d7_nohash_1.wav', '893705bb_nohash_1.wav', '46114b4e_nohash_0.wav', '2a1f4853_nohash_0.wav', 'a3255f5c_nohash_0.wav', 'be91a00a_nohash_0.wav', '35c8fa78_nohash_1.wav', '0ba018fc_nohash_0.wav', '17cc40ee_nohash_0.wav', 'e98cb283_nohash_0.wav', '3ed3e49a_nohash_1.wav', '9aa21fa9_nohash_0.wav', '81a345a3_nohash_0.wav', 'fa446c16_nohash_2.wav', '94e6864f_nohash_2.wav', 'afb9e62e_nohash_0.wav', 'acfd5b5e_nohash_0.wav', 'f0522ff4_nohash_0.wav', '46a153d8_nohash_0.wav', '0ff728b5_nohash_0.wav', 'af7a8296_nohash_0.wav', '2ce7534c_nohash_0.wav', '0397ecda_nohash_0.wav', '4c432947_nohash_1.wav', 'b2e2773a_nohash_0.wav', '5aac2efa_nohash_0.wav', 'f34e6f44_nohash_0.wav', 'c7aa72e6_nohash_0.wav', 'fb2f3242_nohash_0.wav', 'd3d8fcd0_nohash_0.wav', '97e0c576_nohash_2.wav', 'f638a812_nohash_0.wav', '4a1e736b_nohash_0.wav', 'f852895b_nohash_1.wav', '0227998e_nohash_0.wav', '7c9b43f0_nohash_1.wav', '38d78313_nohash_0.wav', 'f568162b_nohash_0.wav', '195c120a_nohash_0.wav', 'cf68fad2_nohash_1.wav', '171b56dc_nohash_0.wav', '24befdb3_nohash_0.wav', 'c98bbbd3_nohash_0.wav', '14df1e28_nohash_0.wav', '7bf801d1_nohash_0.wav', '66041c69_nohash_1.wav', '0c2ca723_nohash_0.wav', 'bdb90d38_nohash_0.wav', '48bdc11c_nohash_0.wav', '1496195a_nohash_0.wav', '6f2f57c1_nohash_0.wav', '18c54a68_nohash_1.wav', '1e412fac_nohash_0.wav', '810c99be_nohash_0.wav', '29229c21_nohash_0.wav', '83c9e7e6_nohash_2.wav', 'a8f45bdc_nohash_0.wav', '34263ab3_nohash_2.wav', '50ed8a7b_nohash_0.wav', '28ce0c58_nohash_0.wav', 'bcf614a2_nohash_0.wav', '6af4aa07_nohash_0.wav', '3a182c98_nohash_0.wav', '56eab10e_nohash_3.wav', 'a4baac4e_nohash_0.wav', 'bd76a7fd_nohash_0.wav', '1b755c65_nohash_0.wav', 'b9cccd01_nohash_0.wav', '7ff4fc72_nohash_0.wav', 'f1eaff75_nohash_0.wav', '7ff085e1_nohash_1.wav', '1c84a139_nohash_0.wav', 'e6515415_nohash_1.wav', 'c6ee87a7_nohash_0.wav', 'fdb5155e_nohash_0.wav', '62b7c848_nohash_1.wav', '15b0c947_nohash_0.wav', 'fc94edb0_nohash_0.wav', '765ffccb_nohash_0.wav', '42398aab_nohash_0.wav', 'a518d1cf_nohash_1.wav', '33903159_nohash_0.wav', '10c6d873_nohash_0.wav', '32efce64_nohash_1.wav', '85851131_nohash_0.wav', 'f7879738_nohash_0.wav', 'cd7f8c1b_nohash_0.wav', '9efe5140_nohash_0.wav', '50033893_nohash_1.wav', 'e6e29c47_nohash_0.wav', 'ddedba85_nohash_3.wav', '569455ff_nohash_0.wav', '19f9c115_nohash_2.wav', 'b1edd209_nohash_0.wav', 'b55a09be_nohash_2.wav', '3f170018_nohash_0.wav', '2dcb6848_nohash_0.wav', '3f45a0cf_nohash_0.wav', '06076b6b_nohash_0.wav', 'd8521ea0_nohash_0.wav', 'b65f6015_nohash_0.wav', 'd486fb84_nohash_0.wav', 'e2b7d6d6_nohash_0.wav', 'fce65496_nohash_0.wav', '13dce503_nohash_1.wav', 'fa57ab3b_nohash_0.wav', '82951cf0_nohash_0.wav', '30a09789_nohash_0.wav', 'f4504600_nohash_0.wav', 'f3d06008_nohash_1.wav', '86402da1_nohash_1.wav', '1995cf9e_nohash_0.wav', '893705bb_nohash_0.wav', '6347b393_nohash_1.wav', 'f3d06008_nohash_0.wav', 'ed3c2d05_nohash_0.wav', 'aba19127_nohash_0.wav', '6b81fead_nohash_2.wav', '8c4854bc_nohash_2.wav', 'a3518e99_nohash_0.wav', 'd2eae23d_nohash_0.wav', '28ed6bc9_nohash_0.wav', '3fb8c268_nohash_0.wav', '62f05757_nohash_0.wav', 'd0f7bef5_nohash_0.wav', 'e9bc5cc2_nohash_0.wav', '85b877b5_nohash_0.wav', '8ec6dab6_nohash_0.wav', 'db24628d_nohash_0.wav', '99fad6a0_nohash_0.wav', 'e55a2b20_nohash_0.wav', 'bf5d409d_nohash_1.wav', '172dc2b0_nohash_1.wav', 'd0fb9ff4_nohash_1.wav', '41dce6f5_nohash_0.wav', '2c727642_nohash_1.wav', 'fc3ba625_nohash_0.wav', '3b195250_nohash_0.wav', '57cb3575_nohash_1.wav', '64da5281_nohash_0.wav', 'a331d9cb_nohash_4.wav', '7e783e3f_nohash_0.wav', '4abefdf5_nohash_0.wav', '9a2e5b3c_nohash_1.wav', '96d8bb6f_nohash_0.wav', '4def68db_nohash_0.wav', 'd0faf7e4_nohash_0.wav', '026290a7_nohash_0.wav', '837f7378_nohash_0.wav', '857366dd_nohash_1.wav', '3ed3e49a_nohash_0.wav', '6205088b_nohash_0.wav', '5c39594f_nohash_0.wav', 'd5cdb23e_nohash_0.wav', '856eb138_nohash_0.wav', '42a99aec_nohash_0.wav', '637c702a_nohash_0.wav', '591d32f3_nohash_0.wav', 'ead2934a_nohash_1.wav', '84bf12ff_nohash_0.wav', '4ca37738_nohash_0.wav', '07089da9_nohash_0.wav', 'bbf38549_nohash_0.wav', '31583d30_nohash_2.wav', 'cfde27ba_nohash_1.wav', 'c9e251d2_nohash_0.wav', '63ae15e4_nohash_1.wav', '3a33d3a4_nohash_0.wav', '126a31d2_nohash_0.wav', '605ed0ff_nohash_1.wav', '1c45ceb2_nohash_0.wav', 'b6ebe225_nohash_0.wav', 'd3f22f0e_nohash_1.wav', 'db9d52d2_nohash_0.wav', '179a61b7_nohash_0.wav', '7d149b38_nohash_0.wav', '365531e2_nohash_0.wav', '747e69fd_nohash_0.wav', 'a19452d5_nohash_2.wav', '11321027_nohash_0.wav', '050170cb_nohash_0.wav', 'df1d5024_nohash_0.wav', '02ade946_nohash_0.wav', 'b8897f1c_nohash_1.wav', '37b03ab1_nohash_1.wav', 'c0e0f834_nohash_2.wav', 'c099668c_nohash_0.wav', 'b7a6f709_nohash_0.wav', 'c205e625_nohash_1.wav', '9b5815cd_nohash_1.wav', 'b1df80c0_nohash_0.wav', 'be7fa0a3_nohash_1.wav', 'f953e1af_nohash_0.wav', 'ec9b830b_nohash_1.wav', 'fa446c16_nohash_1.wav', 'db7c95b0_nohash_1.wav', 'da4ef063_nohash_0.wav', '31d68957_nohash_0.wav', '53fd1780_nohash_0.wav', '23add12a_nohash_0.wav', 'ed07d5b7_nohash_0.wav', 'd1d3e64d_nohash_1.wav', 'a518d1cf_nohash_2.wav', '52e228e9_nohash_0.wav', '66cff190_nohash_0.wav', '9f869f70_nohash_0.wav', '61e50f62_nohash_1.wav', 'dc2222d7_nohash_0.wav', '34ba417a_nohash_1.wav', 'cce17a61_nohash_3.wav', '7b301939_nohash_0.wav', '118261a9_nohash_2.wav', '4a803e67_nohash_0.wav', '9a3f97f8_nohash_0.wav', '79903546_nohash_1.wav', 'a2b16113_nohash_2.wav', '716757ce_nohash_0.wav', '6846af18_nohash_0.wav', 'fbe51750_nohash_0.wav', '1746d7b6_nohash_0.wav', '893705bb_nohash_2.wav', 'ab5d7179_nohash_0.wav', 'fac7deca_nohash_1.wav', 'b25b6065_nohash_0.wav', '4c6944d6_nohash_0.wav', '283d7a53_nohash_0.wav', '5e033479_nohash_1.wav', 'f8f60f59_nohash_0.wav', '7cf14c54_nohash_0.wav', '34e8c726_nohash_1.wav', '18c54a68_nohash_3.wav', 'c8db14a8_nohash_0.wav', '9ce7a419_nohash_0.wav', '3df9a3d4_nohash_1.wav', 'd9d6559e_nohash_0.wav', 'bed06fac_nohash_0.wav', '257e17e0_nohash_0.wav', '2f0a410b_nohash_0.wav', '888a0c49_nohash_0.wav', 'b528edb3_nohash_0.wav', '39ec87ac_nohash_0.wav', 'c50f55b8_nohash_1.wav', 'f21893dc_nohash_0.wav', '2c6d3924_nohash_0.wav', 'f3210686_nohash_0.wav', 'd486fb84_nohash_2.wav', 'bfa63751_nohash_0.wav', '31270cb2_nohash_0.wav', '03c96658_nohash_0.wav', '5b1db3ee_nohash_2.wav', 'f297e878_nohash_0.wav', 'ebdd0f59_nohash_0.wav', '884ae8e1_nohash_0.wav', 'f5d09ebd_nohash_0.wav', '58df33b5_nohash_0.wav', 'db9cfc88_nohash_0.wav', 'bfd26d6b_nohash_0.wav', 'e0315cf6_nohash_0.wav', 'd2dd5785_nohash_0.wav', 'b433332a_nohash_0.wav', '7081436f_nohash_0.wav', '08ab231c_nohash_0.wav', '2c7c33e8_nohash_0.wav', 'ccea893d_nohash_1.wav', '6e2ef3d5_nohash_1.wav', '1a0f9c63_nohash_1.wav', '9e46cfa1_nohash_0.wav', 'ec545975_nohash_1.wav', '2ce7534c_nohash_1.wav', 'f0ebef1b_nohash_0.wav', 'f5e5e8b0_nohash_0.wav', 'c38720cb_nohash_1.wav', 'd9ae8983_nohash_0.wav', 'a16013b7_nohash_0.wav', 'a9abc695_nohash_0.wav', '4beff0c5_nohash_0.wav', '99e6cab8_nohash_1.wav', '6f9088d7_nohash_0.wav', '64220627_nohash_1.wav', '6f2f57c1_nohash_1.wav', '57b38f48_nohash_1.wav', 'ff4ed4f3_nohash_0.wav', 'dce5041a_nohash_0.wav', '6205088b_nohash_2.wav', '8c4854bc_nohash_1.wav', '78884794_nohash_2.wav', 'a6d586b7_nohash_0.wav', 'ca58a8c6_nohash_0.wav', '8b25410a_nohash_0.wav', '09bcdc9d_nohash_0.wav', '857366dd_nohash_0.wav', '324210dd_nohash_0.wav', 'e7334395_nohash_0.wav', '43f57297_nohash_0.wav', '1aed7c6d_nohash_1.wav', 'e6e29c47_nohash_1.wav', '2039b9c1_nohash_0.wav', '80c17118_nohash_0.wav', 'a996cf66_nohash_1.wav', '05b2db80_nohash_0.wav', '0e5193e6_nohash_0.wav', 'c7124b73_nohash_0.wav', '338dacf5_nohash_0.wav', 'f01a0d63_nohash_0.wav', '9bea2ac7_nohash_0.wav', '16fce7de_nohash_0.wav', 'd7529c0c_nohash_0.wav', '2be08ce4_nohash_1.wav', '6fca237d_nohash_0.wav', '6e2ef3d5_nohash_0.wav', '64e48f55_nohash_0.wav', '2d92f18b_nohash_0.wav', '61ab8fbc_nohash_0.wav', 'a24cf51c_nohash_0.wav', '88e85150_nohash_1.wav', 'a527cb3c_nohash_1.wav', 'f0659908_nohash_0.wav', '89f680f3_nohash_2.wav', '616420be_nohash_0.wav', 'f21893dc_nohash_2.wav', '9ab86dd0_nohash_0.wav', '3903b558_nohash_0.wav', '83f9c4ab_nohash_1.wav', '850e2222_nohash_0.wav', 'f88f97a7_nohash_1.wav', '72ca6a6d_nohash_0.wav', 'a9f38bae_nohash_0.wav', '26a093e1_nohash_1.wav', '0b77ee66_nohash_0.wav', 'db9d52d2_nohash_1.wav', 'f9af0887_nohash_0.wav', 'a1dd919f_nohash_0.wav', 'e6327279_nohash_0.wav', '0ea9c8ce_nohash_0.wav', 'ccca5655_nohash_0.wav', 'f1d36c53_nohash_1.wav', '035de8fe_nohash_0.wav', '5705a0f9_nohash_0.wav', '11860c84_nohash_0.wav', 'a331d9cb_nohash_3.wav', '88e85150_nohash_0.wav', 'f4f59743_nohash_0.wav', '2bdbe5f7_nohash_0.wav', '23add12a_nohash_1.wav', '9b3ea809_nohash_0.wav', '3ec05c3d_nohash_0.wav', '187af8be_nohash_0.wav', 'a5609cce_nohash_0.wav', 'c2657ba5_nohash_0.wav', '41777abb_nohash_0.wav', 'c0fb6812_nohash_0.wav', '4874a7e9_nohash_0.wav', '1706c35f_nohash_0.wav', 'b72e58c9_nohash_0.wav', 'dbb7723a_nohash_1.wav', '365908bd_nohash_0.wav', 'de89e2ca_nohash_0.wav', 'c22d3f18_nohash_0.wav', '5be23def_nohash_0.wav', 'cdee383b_nohash_0.wav', '220ee1ef_nohash_0.wav', 'c79159aa_nohash_0.wav', 'a8e25ebb_nohash_0.wav', '3565ca83_nohash_0.wav', '57b38f48_nohash_0.wav', '6d1dcca6_nohash_1.wav', 'd8a5ace5_nohash_0.wav', '0b56bcfe_nohash_0.wav', '0362539c_nohash_0.wav', '210f3aa9_nohash_0.wav', 'c678e0b3_nohash_1.wav', '65f2531f_nohash_0.wav', '1cb788bc_nohash_0.wav', '6f5b4d3d_nohash_0.wav', '129c7d8d_nohash_0.wav', 'a045368c_nohash_0.wav', 'edd8bfe3_nohash_0.wav', '66276b0e_nohash_0.wav', 'f9f9751d_nohash_0.wav', '88e85150_nohash_2.wav', 'b69fe0e2_nohash_0.wav', 'c24d96eb_nohash_0.wav', '5f8097e1_nohash_0.wav', 'a331d9cb_nohash_1.wav', 'ab00c4b2_nohash_1.wav', 'bdee441c_nohash_0.wav', 'ffbb695d_nohash_0.wav', '118261a9_nohash_1.wav', '81a345a3_nohash_1.wav', 'b31ad508_nohash_0.wav', 'ca4d5368_nohash_0.wav', '850e2222_nohash_1.wav', '322d17d3_nohash_0.wav', '161fcca8_nohash_0.wav', 'ce0cb033_nohash_0.wav', 'e269bac0_nohash_0.wav', '8523766b_nohash_0.wav', '1afd49bf_nohash_1.wav', 'c099668c_nohash_1.wav', 'c50225fa_nohash_2.wav', '4fce7686_nohash_0.wav', 'aeb99b1c_nohash_0.wav', 'bcdaa7a9_nohash_0.wav', '97f493b9_nohash_0.wav', 'c1d39ce8_nohash_1.wav', '518588b6_nohash_1.wav', '64da5281_nohash_1.wav', '4d9e07cf_nohash_0.wav', 'd1bf406b_nohash_0.wav', '51f7a034_nohash_0.wav', 'c50f55b8_nohash_4.wav', '8b775397_nohash_0.wav', 'ad1429cf_nohash_0.wav', '3a7d8872_nohash_0.wav', 'b12bef84_nohash_2.wav', '1bb6ed89_nohash_0.wav', 'c5a1e46c_nohash_0.wav', '7f74626f_nohash_0.wav', '3411cf4b_nohash_0.wav', '1474273a_nohash_0.wav', '5744b6a7_nohash_0.wav', 'c0e0f834_nohash_1.wav', 'beb458a4_nohash_0.wav', 'af790082_nohash_0.wav', '7eee5973_nohash_2.wav', '9fa86a74_nohash_1.wav', '652b3da7_nohash_3.wav', '5af0ca83_nohash_0.wav', 'cd68e997_nohash_0.wav', '15f04ff8_nohash_0.wav', '9637f43f_nohash_1.wav', 'c6ca5d01_nohash_1.wav', 'c120e80e_nohash_0.wav', 'dabd70c2_nohash_0.wav', 'd37e4bf1_nohash_0.wav', '1c6e5447_nohash_0.wav', 'bbb2eb5b_nohash_0.wav', 'a2fefcb4_nohash_0.wav', '6f5eea74_nohash_0.wav', '1625acd8_nohash_0.wav', '3bb68054_nohash_0.wav', '9e6bb505_nohash_0.wav', '948867e7_nohash_0.wav', 'c205e625_nohash_0.wav', '3ed3e49a_nohash_3.wav', '8dd24423_nohash_1.wav', 'b308773d_nohash_0.wav', '8a5acefd_nohash_0.wav', '97addd88_nohash_0.wav', '2aca1e72_nohash_0.wav', '4c7c95de_nohash_0.wav', 'd9e9f554_nohash_0.wav', '652b3da7_nohash_0.wav', '55d3725a_nohash_1.wav', '0d82fd99_nohash_0.wav', 'c8771f88_nohash_0.wav', '18a8f03f_nohash_0.wav', 'c885a039_nohash_1.wav', 'b26343e9_nohash_1.wav', '589bce2c_nohash_0.wav', 'b2e2773a_nohash_1.wav', '4e61bf96_nohash_1.wav', '3fdafe25_nohash_0.wav', 'bab36420_nohash_0.wav', '52bfbce8_nohash_0.wav', '1df99a8a_nohash_1.wav', '638548d5_nohash_1.wav', '64a80906_nohash_0.wav', '79903546_nohash_0.wav', '2be08ce4_nohash_0.wav', '161fcca8_nohash_1.wav', '48463cbc_nohash_0.wav', '6d1dcca6_nohash_0.wav', 'd9b50b8b_nohash_1.wav', 'd8c52371_nohash_1.wav', 'fb8c31a9_nohash_0.wav', '4c432947_nohash_0.wav', 'fde2dee7_nohash_0.wav', '5b32733e_nohash_1.wav', 'b69002d4_nohash_0.wav', '6b81fead_nohash_0.wav', '56eab10e_nohash_0.wav', 'e6db3894_nohash_0.wav', 'a8cb6dda_nohash_2.wav', '94de6a6a_nohash_0.wav', '8b367d88_nohash_1.wav', '4bb1244f_nohash_0.wav', '172dc2b0_nohash_0.wav', '1625acd8_nohash_1.wav', 'a6f2fd71_nohash_0.wav', '56eab10e_nohash_1.wav', 'e72aa705_nohash_0.wav', 'd0fb9ff4_nohash_0.wav', '3cdecb0b_nohash_0.wav', 'cce7416f_nohash_0.wav', '39833acb_nohash_0.wav', '9e075bf1_nohash_0.wav', '1474273a_nohash_1.wav', '825f450d_nohash_0.wav', '84d1e469_nohash_0.wav', '590750e8_nohash_0.wav', '063d48cf_nohash_1.wav', '8523766b_nohash_1.wav', '1706c35f_nohash_1.wav', 'cb62dbf1_nohash_0.wav', '274c008f_nohash_0.wav', '40115b19_nohash_0.wav', '0685264e_nohash_0.wav', 'e39a8ddc_nohash_0.wav', '3108acca_nohash_0.wav', '6f342826_nohash_2.wav', 'ddedba85_nohash_0.wav', '20a0d54b_nohash_1.wav', '215699ff_nohash_1.wav', 'cc592808_nohash_2.wav', '3143fdff_nohash_0.wav', '3c257192_nohash_0.wav', '2da58b32_nohash_0.wav', 'cb164eea_nohash_0.wav', 'f7879738_nohash_1.wav', '72aa7259_nohash_0.wav', '6904f0cb_nohash_0.wav', '2d82a556_nohash_1.wav', '2cf28b70_nohash_0.wav', '4f086393_nohash_0.wav', 'bbaa7946_nohash_0.wav', 'edc53350_nohash_0.wav', '5d9bb361_nohash_0.wav', '18a8f03f_nohash_1.wav', 'c1eebc0b_nohash_0.wav', '924c1a04_nohash_1.wav', '62ff07ef_nohash_0.wav', 'f2b8fc18_nohash_0.wav', 'ec545975_nohash_0.wav', '73124b26_nohash_1.wav', '7cbf645a_nohash_0.wav', 'ad6a46f1_nohash_0.wav', 'a331d9cb_nohash_5.wav', 'f1d36c53_nohash_0.wav', 'edd8bfe3_nohash_1.wav', '75b631ff_nohash_0.wav', '5de8f2f0_nohash_0.wav', 'a55105d0_nohash_0.wav', 'fbb56351_nohash_0.wav', '5165cf0a_nohash_0.wav', '32efce64_nohash_2.wav', '35d1b6ee_nohash_0.wav', 'b6091c84_nohash_0.wav']]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "p6l11Cvr1LN6"
      },
      "source": [
        "# Check ground truth Y vector\n",
        "\n",
        "print(y)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QufjXdIr1OmA",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "705a80dc-db90-4ff6-92e3-d4d85696db16"
      },
      "source": [
        "# Flatten filename and y vectors\n",
        "\n",
        "filenames = [item for sublist in filenames for item in sublist]\n",
        "y = [item for sublist in y for item in sublist]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
            "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
            "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
            "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
            "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
            "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
            "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
            "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
            "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
            "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
            "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
            "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
            "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
            "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
            "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
            "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
            "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
            "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
            "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
            "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
            "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
            "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
            "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
            "       0., 0., 0., 0., 0., 0., 0., 0.]), array([1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
            "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
            "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
            "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
            "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
            "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
            "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
            "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
            "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
            "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
            "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
            "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
            "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
            "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
            "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
            "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
            "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
            "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
            "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
            "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
            "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
            "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
            "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,\n",
            "       1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.]), array([2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2.,\n",
            "       2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2.,\n",
            "       2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2.,\n",
            "       2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2.,\n",
            "       2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2.,\n",
            "       2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2.,\n",
            "       2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2.,\n",
            "       2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2.,\n",
            "       2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2.,\n",
            "       2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2.,\n",
            "       2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2.,\n",
            "       2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2.,\n",
            "       2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2.,\n",
            "       2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2.,\n",
            "       2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2.,\n",
            "       2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2.,\n",
            "       2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2.,\n",
            "       2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2.,\n",
            "       2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2.,\n",
            "       2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2.,\n",
            "       2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2.,\n",
            "       2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2.,\n",
            "       2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2.,\n",
            "       2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2., 2.]), array([3., 3., 3., ..., 3., 3., 3.]), array([4., 4., 4., ..., 4., 4., 4.]), array([5., 5., 5., ..., 5., 5., 5.]), array([6., 6., 6., ..., 6., 6., 6.]), array([7., 7., 7., ..., 7., 7., 7.]), array([8., 8., 8., ..., 8., 8., 8.]), array([9., 9., 9., ..., 9., 9., 9.]), array([10., 10., 10., ..., 10., 10., 10.]), array([11., 11., 11., ..., 11., 11., 11.]), array([12., 12., 12., ..., 12., 12., 12.]), array([13., 13., 13., ..., 13., 13., 13.]), array([14., 14., 14., ..., 14., 14., 14.]), array([15., 15., 15., ..., 15., 15., 15.]), array([16., 16., 16., ..., 16., 16., 16.]), array([17., 17., 17., ..., 17., 17., 17.]), array([18., 18., 18., ..., 18., 18., 18.]), array([19., 19., 19., ..., 19., 19., 19.]), array([20., 20., 20., ..., 20., 20., 20.]), array([21., 21., 21., ..., 21., 21., 21.]), array([22., 22., 22., ..., 22., 22., 22.]), array([23., 23., 23., ..., 23., 23., 23.]), array([24., 24., 24., ..., 24., 24., 24.]), array([25., 25., 25., ..., 25., 25., 25.]), array([26., 26., 26., ..., 26., 26., 26.]), array([27., 27., 27., ..., 27., 27., 27.]), array([28., 28., 28., ..., 28., 28., 28.]), array([29., 29., 29., ..., 29., 29., 29.]), array([30., 30., 30., ..., 30., 30., 30.]), array([31., 31., 31., ..., 31., 31., 31.]), array([32., 32., 32., ..., 32., 32., 32.]), array([33., 33., 33., ..., 33., 33., 33.]), array([34., 34., 34., ..., 34., 34., 34.]), array([35., 35., 35., ..., 35., 35., 35.]), array([36., 36., 36., ..., 36., 36., 36.]), array([37., 37., 37., ..., 37., 37., 37.])]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YzdQqovv-2sJ",
        "outputId": "f755e77d-d738-4ab9-d5ad-2dcc1d7493d0"
      },
      "source": [
        "filenames[0:5]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['pink_noise_38.wav',\n",
              " 'dude_miaowing_2.wav',\n",
              " 'dude_miaowing_1.wav',\n",
              " 'doing_the_dishes_32.wav',\n",
              " 'exercise_bike_6.wav']"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "I_ijSeS1-50V",
        "outputId": "36fa9d2d-efd1-4484-b975-1d4e146e67a3"
      },
      "source": [
        "y[0:5]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[0.0, 0.0, 0.0, 0.0, 0.0]"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Create variables for C files"
      ],
      "metadata": {
        "id": "73oPADn6jD4c"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Generate the dictionary\n",
        "\n",
        "for target in all_targets:\n",
        "  print(target.upper(), end = \",\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "F5Z4NoWRYDzt",
        "outputId": "ef3a88fc-b231-4594-aa20-a7064493a885"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "_BACKGROUND_NOISE_,_SILENCE_,_UNKNOWN_,BACKWARD,BED,BIRD,CAT,DOG,DOWN,EIGHT,FIVE,FOLLOW,FORWARD,FOUR,GO,HAPPY,HOUSE,LEARN,LEFT,MARVIN,NINE,NO,OFF,ON,ONE,RIGHT,SEVEN,SHEILA,SIX,STOP,THREE,TREE,TWO,UP,VISUAL,WOW,YES,ZERO,"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Create extern constants\n",
        "\n",
        "for w in all_targets:\n",
        "  print(f\"extern const char {w.upper()}[];\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DcMotmR3jI6S",
        "outputId": "1bba3374-eca9-4de0-d265-a293dfa9ecf4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "extern const char _BACKGROUND_NOISE_[];\n",
            "extern const char _SILENCE_[];\n",
            "extern const char _UNKNOWN_[];\n",
            "extern const char BACKWARD[];\n",
            "extern const char BED[];\n",
            "extern const char BIRD[];\n",
            "extern const char CAT[];\n",
            "extern const char DOG[];\n",
            "extern const char DOWN[];\n",
            "extern const char EIGHT[];\n",
            "extern const char FIVE[];\n",
            "extern const char FOLLOW[];\n",
            "extern const char FORWARD[];\n",
            "extern const char FOUR[];\n",
            "extern const char GO[];\n",
            "extern const char HAPPY[];\n",
            "extern const char HOUSE[];\n",
            "extern const char LEARN[];\n",
            "extern const char LEFT[];\n",
            "extern const char MARVIN[];\n",
            "extern const char NINE[];\n",
            "extern const char NO[];\n",
            "extern const char OFF[];\n",
            "extern const char ON[];\n",
            "extern const char ONE[];\n",
            "extern const char RIGHT[];\n",
            "extern const char SEVEN[];\n",
            "extern const char SHEILA[];\n",
            "extern const char SIX[];\n",
            "extern const char STOP[];\n",
            "extern const char THREE[];\n",
            "extern const char TREE[];\n",
            "extern const char TWO[];\n",
            "extern const char UP[];\n",
            "extern const char VISUAL[];\n",
            "extern const char WOW[];\n",
            "extern const char YES[];\n",
            "extern const char ZERO[];\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Create constant strings\n",
        "\n",
        "for w in all_targets:\n",
        "  print(f\"const char {w.upper()}[] = \\\"{w}\\\";\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "17bUQ2PIX0Vo",
        "outputId": "ef04e41f-569a-440f-a352-c0f887e8d9eb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "const char _BACKGROUND_NOISE_[] = \"_background_noise_\";\n",
            "const char _SILENCE_[] = \"_silence_\";\n",
            "const char _UNKNOWN_[] = \"_unknown_\";\n",
            "const char BACKWARD[] = \"backward\";\n",
            "const char BED[] = \"bed\";\n",
            "const char BIRD[] = \"bird\";\n",
            "const char CAT[] = \"cat\";\n",
            "const char DOG[] = \"dog\";\n",
            "const char DOWN[] = \"down\";\n",
            "const char EIGHT[] = \"eight\";\n",
            "const char FIVE[] = \"five\";\n",
            "const char FOLLOW[] = \"follow\";\n",
            "const char FORWARD[] = \"forward\";\n",
            "const char FOUR[] = \"four\";\n",
            "const char GO[] = \"go\";\n",
            "const char HAPPY[] = \"happy\";\n",
            "const char HOUSE[] = \"house\";\n",
            "const char LEARN[] = \"learn\";\n",
            "const char LEFT[] = \"left\";\n",
            "const char MARVIN[] = \"marvin\";\n",
            "const char NINE[] = \"nine\";\n",
            "const char NO[] = \"no\";\n",
            "const char OFF[] = \"off\";\n",
            "const char ON[] = \"on\";\n",
            "const char ONE[] = \"one\";\n",
            "const char RIGHT[] = \"right\";\n",
            "const char SEVEN[] = \"seven\";\n",
            "const char SHEILA[] = \"sheila\";\n",
            "const char SIX[] = \"six\";\n",
            "const char STOP[] = \"stop\";\n",
            "const char THREE[] = \"three\";\n",
            "const char TREE[] = \"tree\";\n",
            "const char TWO[] = \"two\";\n",
            "const char UP[] = \"up\";\n",
            "const char VISUAL[] = \"visual\";\n",
            "const char WOW[] = \"wow\";\n",
            "const char YES[] = \"yes\";\n",
            "const char ZERO[] = \"zero\";\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Training, validation and test splits"
      ],
      "metadata": {
        "id": "tuGUarmpjpDE"
      }
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MQb2cAjW1RUV"
      },
      "source": [
        "# Associate filenames with true output and shuffle\n",
        "\n",
        "filenames_y = list(zip(filenames, y))\n",
        "random.shuffle(filenames_y)\n",
        "filenames, y = zip(*filenames_y)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZMWrrQkPNfJV"
      },
      "source": [
        "# Validation and test percentage\n",
        "\n",
        "val_ratio = 0.1\n",
        "test_ratio = 0.1"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DtHMq0iX1hv1",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "2582f55a-4585-4895-9a9a-b5b997eba63f"
      },
      "source": [
        "# Calculate validation and test set sizes\n",
        "\n",
        "val_set_size = int(len(filenames) * val_ratio)\n",
        "test_set_size = int(len(filenames) * test_ratio)\n",
        "print(f\"Validation size {val_set_size}\\ntTest set size {test_set_size}\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Validation size 10704\n",
            "tTest set size 10704\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "eBDcj2YV1kOj"
      },
      "source": [
        "# Break dataset apart into train, validation, and test sets\n",
        "\n",
        "filenames_val = filenames[:val_set_size]\n",
        "filenames_test = filenames[val_set_size:(val_set_size + test_set_size)]\n",
        "filenames_train = filenames[(val_set_size + test_set_size):]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KZNrgVf61mQ3"
      },
      "source": [
        "# Break y apart into train, validation, and test sets\n",
        "\n",
        "y_orig_val = y[:val_set_size]\n",
        "y_orig_test = y[val_set_size:(val_set_size + test_set_size)]\n",
        "y_orig_train = y[(val_set_size + test_set_size):]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yXr8gX9U1oJo"
      },
      "source": [
        "def calc_mfcc(path: str, debug: bool = False) -> np.ndarray:\n",
        "  \"\"\"Creates a matrix of MFCCs from the given input file.\n",
        "  \n",
        "  Args:\n",
        "    path: the path to the file to extract MFCCs from\n",
        "    debug: whenever to print signal shape or sampling rate\n",
        "\n",
        "  Returns:\n",
        "    An ndarray of shape (n_mffc, n_frames)\n",
        "  \"\"\"\n",
        "\n",
        "  signal, fs = librosa.load(path, sr=sample_rate)\n",
        "  if debug:\n",
        "    print(f\"DEBUG (calc_mfcc): signal shape={signal.shape}, sampling rate={fs}\")\n",
        "\n",
        "  # By default, n_fft=2048, hop_length=512\n",
        "  mfccs = librosa.feature.mfcc(signal, \n",
        "                               sr=fs, \n",
        "                               n_mfcc=num_mfcc, \n",
        "                               dct_type=2, \n",
        "                               norm='ortho', \n",
        "                               lifter=0, \n",
        "                               center=False)\n",
        "  \n",
        "  return mfccs"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "a-9nQZqLbLT9",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "dd0b9916-3a93-4fce-9506-536c02140765"
      },
      "source": [
        "# TEST: Construct test set by computing MFCC of each WAV file\n",
        "\n",
        "prob_cnt = 0\n",
        "x_test = []\n",
        "y_test = []\n",
        "max_index_ = 100\n",
        "\n",
        "for index, filename in enumerate(filenames_train):\n",
        "\n",
        "    # Stop after `max_index_` iteration\n",
        "    if index >= max_index_:\n",
        "        break\n",
        "    \n",
        "    # Create path from given filename and target item\n",
        "    path = join(dataset_path, \n",
        "                target_list[int(y_orig_train[index])], \n",
        "                filename)\n",
        "    \n",
        "    # Create MFCCs\n",
        "    mfccs = calc_mfcc(path)\n",
        "\n",
        "    # Keep only the MFCCs with the correct number of frames\n",
        "    if mfccs.shape[1] == len_mfcc:\n",
        "        x_test.append(mfccs)\n",
        "        y_test.append(y_orig_train[index])\n",
        "    else:\n",
        "        print('Dropped:', index, mfccs.shape)\n",
        "        prob_cnt += 1"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Dropped: 21 (16, 17)\n",
            "Dropped: 38 (16, 15)\n",
            "Dropped: 42 (16, 20)\n",
            "Dropped: 43 (16, 20)\n",
            "Dropped: 61 (16, 27)\n",
            "Dropped: 66 (16, 20)\n",
            "Dropped: 99 (16, 25)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Z9uuGpx9bNF3",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "b8c2aca6-af51-40a2-8e38-498665cb9f50"
      },
      "source": [
        "print('% of problematic samples:', prob_cnt / max_index_)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "% of problematic samples: 0.07\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pvBLt7d61vJQ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "54a0348d-10fa-4e3c-88df-57a5bc974a38"
      },
      "source": [
        "# TEST: Test shorter MFCC\n",
        "\n",
        "idx = 41\n",
        "\n",
        "# Create path from given filename and target item\n",
        "path = join(dataset_path, \n",
        "            target_list[int(y_orig_train[idx])], \n",
        "            filenames_train[idx])\n",
        "\n",
        "# Create MFCCs\n",
        "mfccs = calc_mfcc(path)\n",
        "print(\"MFCCs:\", mfccs)\n",
        "\n",
        "# Plot MFCC\n",
        "fig = plt.figure()\n",
        "plt.imshow(mfccs, cmap='inferno', origin='lower')\n",
        "\n",
        "# Play wav file\n",
        "print(target_list[int(y_orig_train[idx])])\n",
        "AudioSegment.from_file(path, format=\"wav\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "MFCCs: [[-5.03652771e+02 -5.00809998e+02 -4.98350372e+02 -4.93565399e+02\n",
            "  -4.96061462e+02 -4.93485291e+02 -4.22364746e+02 -2.89137878e+02\n",
            "  -2.22479492e+02 -2.07666214e+02 -2.24270065e+02 -2.35980179e+02\n",
            "  -2.49901352e+02 -2.54737198e+02 -2.78789154e+02 -2.81649841e+02\n",
            "  -2.83572144e+02 -2.99197021e+02 -3.16042297e+02 -3.23233551e+02\n",
            "  -3.33626526e+02 -3.67338593e+02 -4.09591156e+02 -4.50205078e+02\n",
            "  -4.74049347e+02 -4.93636047e+02 -5.01333466e+02 -4.99804596e+02]\n",
            " [ 1.48942352e+02  1.46874756e+02  1.47087372e+02  1.55038574e+02\n",
            "   1.53257355e+02  1.54061584e+02  1.55888763e+02  1.53006378e+02\n",
            "   1.48538696e+02  1.36297913e+02  1.29636047e+02  1.32023254e+02\n",
            "   1.29189194e+02  1.31279114e+02  1.23992737e+02  7.82488632e+01\n",
            "   5.17302399e+01  4.88455048e+01  4.17787704e+01  4.53148117e+01\n",
            "   6.14215088e+01  7.18253021e+01  9.09879913e+01  1.19209190e+02\n",
            "   1.34862122e+02  1.45926941e+02  1.46873260e+02  1.49139435e+02]\n",
            " [ 1.28372993e+01  8.85721684e+00  7.66126633e+00  9.65583801e+00\n",
            "   1.03204088e+01  1.07733431e+01  1.09947729e+00 -1.04673405e+01\n",
            "  -1.77797699e+01 -2.59686947e+01 -2.67363148e+01 -2.02414894e+01\n",
            "  -1.50795593e+01 -1.70210552e+01 -1.69615479e+01 -2.02984467e+01\n",
            "  -1.57519760e+01 -7.90961742e+00 -1.00012245e+01 -1.26068325e+01\n",
            "  -5.90323496e+00  3.22188306e+00  5.33772945e+00  4.35976124e+00\n",
            "   1.15600843e+01  1.21257534e+01  1.57463417e+01  1.40707569e+01]\n",
            " [ 5.96088839e+00  7.87621784e+00  9.63546085e+00  4.75255919e+00\n",
            "   2.61419201e+00  1.34856200e+00 -1.50284977e+01 -1.59343452e+01\n",
            "  -5.99702406e+00 -3.58975148e+00  1.33583927e+00 -2.59061992e-01\n",
            "  -1.50409520e-01 -1.42407684e+01 -1.83619690e+01 -1.01048069e+01\n",
            "   1.00285065e+00  2.33875775e+00  1.81707454e+00  2.49034882e+00\n",
            "   1.21876860e+01  2.00608215e+01  1.14163609e+01  5.80841541e+00\n",
            "   9.85703087e+00  1.35227242e+01  1.71706333e+01  1.44031353e+01]\n",
            " [ 7.14660978e+00  1.05158749e+01  9.73422909e+00  9.45822811e+00\n",
            "   4.00831032e+00  1.69701290e+00 -4.86461143e+01 -8.49498138e+01\n",
            "  -9.23310013e+01 -9.44800797e+01 -9.61380768e+01 -1.03263962e+02\n",
            "  -9.82151184e+01 -8.66914825e+01 -5.94979553e+01 -3.45667152e+01\n",
            "  -2.11337128e+01 -9.61554909e+00 -9.56915474e+00 -1.09885216e+01\n",
            "  -4.75910950e+00 -4.63378716e+00 -8.02789116e+00 -4.03858852e+00\n",
            "   7.15848160e+00  9.23989010e+00  1.17043781e+01  1.54672689e+01]\n",
            " [-7.80720472e+00 -8.02683830e+00 -1.14732800e+01 -1.00209618e+01\n",
            "  -1.25951014e+01 -1.63417606e+01 -2.13367057e+00 -1.07018209e+00\n",
            "  -5.14048719e+00 -6.83081913e+00 -1.16872416e+01 -1.41077261e+01\n",
            "   1.77734423e+00  1.31078939e+01  9.22406960e+00  8.95922899e-01\n",
            "  -3.38726473e+00 -2.31904936e+00  8.05448914e+00  1.02430305e+01\n",
            "   1.29762020e+01  8.73742867e+00  5.83727264e+00  1.68520319e+00\n",
            "  -5.34368420e+00 -9.48698997e+00 -1.08847494e+01 -2.46572781e+00]\n",
            " [-1.23572264e+01 -1.42790871e+01 -1.39012527e+01 -1.41479416e+01\n",
            "  -1.35629292e+01 -1.32141895e+01 -1.99851751e+00  4.72007084e+00\n",
            "   9.17830563e+00  7.06437445e+00  5.71951580e+00  1.00184956e+01\n",
            "   1.38760815e+01  1.10062828e+01  2.82569647e-01 -9.81666565e+00\n",
            "  -1.16523638e+01 -1.40247021e+01 -1.28330803e+01 -1.40498333e+01\n",
            "  -1.57448997e+01 -1.73577633e+01 -1.59271393e+01 -1.68554764e+01\n",
            "  -1.79884644e+01 -1.40827770e+01 -1.16781092e+01 -7.78895283e+00]\n",
            " [-1.27354298e+01 -1.11771126e+01 -6.73685789e+00 -6.65629005e+00\n",
            "  -1.19263144e+01 -7.95538092e+00 -4.04898047e-01  1.03401527e+01\n",
            "   2.26138115e+01  3.29029007e+01  3.35377998e+01  2.52209148e+01\n",
            "   1.09319134e+01  5.92123795e+00  9.26850319e+00  8.91213417e+00\n",
            "   1.33661985e+01  1.50228825e+01  1.15246868e+01  9.11032677e+00\n",
            "   4.22459269e+00 -2.56917953e-01  3.05032253e+00 -2.36240298e-01\n",
            "  -7.57797718e-01  1.82921052e+00 -2.43084860e+00 -6.84153080e+00]\n",
            " [-1.77615986e+01 -1.56099129e+01 -9.28250122e+00 -1.31473265e+01\n",
            "  -2.00233612e+01 -1.80034485e+01 -1.18816519e+01 -1.73071136e+01\n",
            "  -2.04574394e+01 -1.86324120e+01 -1.77185211e+01 -1.98908768e+01\n",
            "  -1.07501621e+01 -5.39995670e+00 -7.71215153e+00 -9.86617088e+00\n",
            "  -2.05766296e+01 -2.68830147e+01 -2.08618412e+01 -2.15615406e+01\n",
            "  -2.27055569e+01 -2.45490189e+01 -2.08088722e+01 -1.88766880e+01\n",
            "  -1.06380091e+01 -7.55620670e+00 -1.02406111e+01 -1.41970558e+01]\n",
            " [-1.91241035e+01 -1.89342709e+01 -1.03078070e+01 -1.72608147e+01\n",
            "  -1.89231834e+01 -1.50666637e+01 -1.49313908e+01  7.84990978e+00\n",
            "   1.18857727e+01  1.30863838e+01  1.37502270e+01  7.67361975e+00\n",
            "   6.87246704e+00  1.39879942e+01  2.11544838e+01  1.51681232e+01\n",
            "   9.92167091e+00  1.00696926e+01  7.04356194e+00  5.03210640e+00\n",
            "   5.76147842e+00  4.52907801e+00 -1.54104114e+00 -1.36261492e+01\n",
            "  -1.16675901e+01 -1.23812904e+01 -1.60073776e+01 -1.81240768e+01]\n",
            " [-6.29494858e+00 -7.17054319e+00 -3.62483454e+00 -8.92649269e+00\n",
            "  -1.32677479e+01 -1.13991003e+01 -1.33229694e+01 -1.20626450e+01\n",
            "  -1.46894665e+01 -1.45509062e+01 -1.09259844e+01 -1.11403322e+01\n",
            "  -8.10586548e+00 -1.27253895e+01 -1.52561502e+01 -2.18481789e+01\n",
            "  -2.04146423e+01 -1.65587273e+01 -1.77183418e+01 -1.50986567e+01\n",
            "  -1.56767750e+01 -1.86658440e+01 -1.48048668e+01 -1.11384897e+01\n",
            "  -1.03914070e+01 -7.45249939e+00 -6.90540028e+00 -8.72125626e+00]\n",
            " [-7.61393642e+00 -8.47092056e+00 -1.14264698e+01 -1.20849419e+01\n",
            "  -1.40096369e+01 -1.54637690e+01 -4.80879784e+00  5.60769367e+00\n",
            "   1.02433596e+01  8.57779121e+00  2.61959696e+00  5.91030240e-01\n",
            "   9.27097261e-01 -1.78282785e+00 -4.00311136e+00  3.32076931e+00\n",
            "   1.04060669e+01  7.45556450e+00  3.00136089e+00  2.64389253e+00\n",
            "  -1.11494863e+00 -3.59917450e+00 -1.96855688e+00 -1.23841343e+01\n",
            "  -1.57660923e+01 -1.56924782e+01 -1.03772449e+01 -8.69810772e+00]\n",
            " [-1.29166784e+01 -1.22496862e+01 -1.43432951e+01 -1.35315285e+01\n",
            "  -1.35752707e+01 -1.36842175e+01 -7.56441975e+00 -1.36979656e+01\n",
            "  -1.78468246e+01 -1.66851482e+01 -1.50456657e+01 -1.37934837e+01\n",
            "  -1.73102264e+01 -1.82928543e+01 -2.35508137e+01 -2.94992485e+01\n",
            "  -2.64897766e+01 -2.29886951e+01 -2.78679752e+01 -3.27537231e+01\n",
            "  -3.30201569e+01 -2.99322491e+01 -2.44333172e+01 -1.81268768e+01\n",
            "  -1.52149582e+01 -1.06405592e+01 -9.25231838e+00 -6.74161386e+00]\n",
            " [-7.24123001e+00 -3.62319565e+00 -1.03398190e+01 -1.15990763e+01\n",
            "  -1.04403000e+01 -1.03468437e+01 -1.30821714e+01 -8.74087048e+00\n",
            "  -3.46828532e+00  3.44643664e+00  1.86979508e+00 -5.82384253e+00\n",
            "  -3.88882113e+00 -9.02252197e+00 -7.10980463e+00 -3.63301945e+00\n",
            "  -2.65766001e+00  1.12332904e+00  2.39097309e+00 -1.76524401e-01\n",
            "  -3.30974609e-01 -1.71790755e+00 -4.51245737e+00 -1.66541457e+00\n",
            "   8.27910721e-01 -4.89975023e+00 -1.19341969e-01 -1.85396624e+00]\n",
            " [-1.01260052e+01 -5.49323082e+00 -1.09025154e+01 -9.40400314e+00\n",
            "  -5.78485680e+00 -8.88082695e+00 -1.80012951e+01 -2.62671127e+01\n",
            "  -2.40110683e+01 -2.14506779e+01 -2.01701317e+01 -2.11073742e+01\n",
            "  -2.33930473e+01 -2.29268532e+01 -1.53770409e+01 -1.23824673e+01\n",
            "  -1.42251015e+01 -1.14383745e+01 -1.20927124e+01 -1.39113140e+01\n",
            "  -1.20214043e+01 -1.06982622e+01 -9.75106621e+00 -5.16563511e+00\n",
            "  -5.02685404e+00 -3.13389897e+00 -1.97967505e+00 -6.30167627e+00]\n",
            " [-1.17775621e+01 -9.24646378e+00 -8.27833557e+00 -8.37378979e+00\n",
            "  -1.01733961e+01 -1.30488892e+01 -1.55802736e+01 -1.39404612e+01\n",
            "  -1.20111580e+01 -9.45646477e+00 -6.25278854e+00 -4.07005548e+00\n",
            "  -7.92982042e-01 -3.90547693e-01  9.55395103e-01  7.18395615e+00\n",
            "   1.01539249e+01  1.37978554e+01  9.74965477e+00  4.94169807e+00\n",
            "   4.66819584e-01 -4.96687031e+00 -5.77341652e+00 -5.24674416e+00\n",
            "  -2.11130571e+00 -7.68044758e+00 -6.39443398e+00 -7.24276924e+00]]\n",
            "off\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "                    <audio controls>\n",
              "                        <source src=\"data:audio/mpeg;base64,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\" type=\"audio/mpeg\"/>\n",
              "                        Your browser does not support the audio element.\n",
              "                    </audio>\n",
              "                  "
            ],
            "text/plain": [
              "<pydub.audio_segment.AudioSegment at 0x7fad3a7c1590>"
            ]
          },
          "metadata": {},
          "execution_count": 27
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Hha1YUIbC42x"
      },
      "source": [
        "def to_word(out_value):\n",
        "    \"\"\"Converts the outuput value of the model to the corresponding word.\"\"\"\n",
        "\n",
        "    return target_list[int(out_value)]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_SkfEAn11xdB"
      },
      "source": [
        "def extract_features(in_files: T.List[str], \n",
        "                     in_y: T.List[float]) -> T.List[np.ndarray]:\n",
        "    \"\"\"Computes a dataset of MFCC from the given input files, and associate them\n",
        "    with the ground truth values.\n",
        "    \n",
        "    If the size of sample frames is less than the target one, then the sample \n",
        "    will be discarded.\n",
        "\n",
        "    Args:\n",
        "      in_files: list of wav files\n",
        "      in_y: the ground truth values of the files in `in_files`\n",
        "\n",
        "    Returns:\n",
        "      A list of np.ndarray containing the MFCCs extracted from `in_files`\n",
        "    \"\"\"\n",
        "\n",
        "    prob_cnt = 0\n",
        "    out_x = []\n",
        "    out_y = []\n",
        "        \n",
        "    for index, filename in tqdm(enumerate(in_files), total=len(in_files)):\n",
        "      \n",
        "        # Create path from given filename and target item\n",
        "        path = join(dataset_path,\n",
        "                    target_list[int(in_y[index])], \n",
        "                    filename)\n",
        "        \n",
        "        # Check to make sure we're reading a .wav file\n",
        "        if not path.endswith('.wav'):\n",
        "            continue\n",
        "\n",
        "        # Create MFCCs\n",
        "        mfccs = calc_mfcc(path)\n",
        "\n",
        "        # Only keep MFCCs with the correct number of frames\n",
        "        if mfccs.shape[1] == len_mfcc:\n",
        "            out_x.append(mfccs)\n",
        "            out_y.append(in_y[index])\n",
        "        else: \n",
        "            prob_cnt += 1\n",
        "            \n",
        "    return out_x, out_y, prob_cnt"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7Jj0SqmP1zyz",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "6d91036a-c7e7-41c8-e543-ce2a5e9f69fd"
      },
      "source": [
        "# Create train, validation, and test sets\n",
        "\n",
        "x_train, y_train, prob = extract_features(filenames_train, \n",
        "                                          y_orig_train)\n",
        "print('Removed percentage:', prob / len(y_orig_train))\n",
        "\n",
        "x_val, y_val, prob = extract_features(filenames_val, y_orig_val)\n",
        "print('Removed percentage:', prob / len(y_orig_val))\n",
        "\n",
        "x_test, y_test, prob = extract_features(filenames_test, y_orig_test)\n",
        "print('Removed percentage:', prob / len(y_orig_test))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 85636/85636 [12:58<00:00, 110.02it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Removed percentage: 0.09778597785977859\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 10704/10704 [01:37<00:00, 109.49it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Removed percentage: 0.09828101644245142\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 10704/10704 [01:38<00:00, 108.41it/s]"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Removed percentage: 0.09332959641255606\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "n2d7XX9WBEhB"
      },
      "source": [
        "# Save features and truth vector (y) sets to disk\n",
        "\n",
        "np.savez(feature_sets_file, \n",
        "         x_train=x_train, \n",
        "         y_train=y_train, \n",
        "         x_val=x_val, \n",
        "         y_val=y_val, \n",
        "         x_test=x_test, \n",
        "         y_test=y_test)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Create the model"
      ],
      "metadata": {
        "id": "PnEChVNKY84K"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Load dataset back"
      ],
      "metadata": {
        "id": "37iPMdz0kZaq"
      }
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tiUxt5CW13cs",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "fc22ead7-427f-4e43-8078-e474e9332559"
      },
      "source": [
        "# Load features\n",
        "\n",
        "feature_sets = np.load(feature_sets_file)\n",
        "feature_sets.files"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['x_train', 'y_train', 'x_val', 'y_val', 'x_test', 'y_test']"
            ]
          },
          "metadata": {},
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "v5LTEeLI2LhJ"
      },
      "source": [
        "# Assign feature sets\n",
        "\n",
        "x_train = feature_sets['x_train']\n",
        "y_train = feature_sets['y_train']\n",
        "x_val = feature_sets['x_val']\n",
        "y_val = feature_sets['y_val']\n",
        "x_test = feature_sets['x_test']\n",
        "y_test = feature_sets['y_test']"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Concatenate training and validation sets, since they will be splitted in\n",
        "# stratified manner in the next steps\n",
        "\n",
        "X = np.concatenate((x_train, x_val))\n",
        "y = np.concatenate((y_train, y_val))\n",
        "\n",
        "print(f\"X shape: {X.shape}, y shape: {y.shape}\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "spXEP7Bz4KkB",
        "outputId": "f49bfbb0-be88-44a5-b142-fa368fd69fd2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "X shape: (86913, 16, 28), y shape: (86913,)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "A24dbEDdOlqE",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "d8fab765-5b9b-4597-a741-5f3ea905f78c"
      },
      "source": [
        "# Number of unique labels. When the whole dataset is loaded, it should be 38.\n",
        "\n",
        "n_labels = np.max([len(np.unique(y_test)), \n",
        "                   len(np.unique(y))])\n",
        "\n",
        "n_labels"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "38"
            ]
          },
          "metadata": {},
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "aHXFpAhh9riv"
      },
      "source": [
        "# Settings\n",
        "\n",
        "model_filename = 'speech-commands-model.h5'\n",
        "keras_model_filename = '/content/speech-commands-model.h5'\n",
        "tflite_filename = '/content/speech-commands-model.tflite'"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sziKLpyV2aRF",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "6cd9ca79-4a8a-412f-bed7-00a32519359c"
      },
      "source": [
        "# CNN for TF expects (batch, height, width, channels)\n",
        "# So we reshape the input tensors with a \"color\" channel of 1\n",
        "\n",
        "x_test = x_test.reshape(x_test.shape[0], \n",
        "                        x_test.shape[1], \n",
        "                        x_test.shape[2], \n",
        "                        1)\n",
        "\n",
        "X = X.reshape(X.shape[0], \n",
        "              X.shape[1], \n",
        "              X.shape[2], \n",
        "              1)\n",
        "\n",
        "print(x_test.shape)\n",
        "print(X.shape)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(9705, 16, 28, 1)\n",
            "(86913, 16, 28, 1)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2Duh8HLz2f5P",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c66f44ad-5fb4-4d67-cf38-2403ad041ca8"
      },
      "source": [
        "# Input shape for CNN is size of MFCC of 1 sample\n",
        "\n",
        "input_shape = X.shape[1:]\n",
        "print(input_shape)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(16, 28, 1)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Define the model"
      ],
      "metadata": {
        "id": "08jkNIrukgmD"
      }
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "R0eI_3q6-H7H"
      },
      "source": [
        "from tensorflow.keras import layers, models, regularizers"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def create_model(verbose: int =0):\n",
        "  \"\"\"Creates and build a CNN model.\n",
        "\n",
        "  Args:\n",
        "    verbose: the verbosity of the output\n",
        "\n",
        "  Returns:\n",
        "    the CNN model already complied.\n",
        "  \"\"\"\n",
        "  # build network\n",
        "  model = models.Sequential()\n",
        "\n",
        "  # conv layer 1\n",
        "  model.add(layers.Conv2D(8,\n",
        "                          (3, 3), \n",
        "                          activation=\"relu\", \n",
        "                          input_shape=input_shape))\n",
        "  # conv layer 2\n",
        "  model.add(layers.Conv2D(8,\n",
        "                          (3, 3), \n",
        "                          activation=\"relu\"))\n",
        "  model.add(layers.MaxPool2D((2,2)))\n",
        "  model.add(layers.Dropout(0.1))\n",
        "\n",
        "  model.add(layers.Flatten())\n",
        "\n",
        "  model.add(layers.Dense(64))\n",
        "  model.add(layers.Dropout(0.16))\n",
        "  model.add(layers.Activation(\"relu\"))\n",
        "\n",
        "  model.add(layers.Dense(64))\n",
        "  model.add(layers.Dropout(0.12))\n",
        "  model.add(layers.Activation(\"relu\"))\n",
        "\n",
        "  #softmax classifier\n",
        "  model.add(layers.Dense(n_labels))\n",
        "  model.add(layers.Activation(\"softmax\"))\n",
        "\n",
        "  #compile model\n",
        "  model.compile(\n",
        "      optimizer=tf.keras.optimizers.Adam(), \n",
        "      loss=tf.keras.losses.SparseCategoricalCrossentropy(), \n",
        "      metrics=[\"accuracy\"],\n",
        "  ) \n",
        "\n",
        "  if verbose > 0:\n",
        "    model.summary()\n",
        "\n",
        "  return model"
      ],
      "metadata": {
        "id": "5TR19Jvol42h"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Cross Validation"
      ],
      "metadata": {
        "id": "R7sIs5ySxXSq"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def cross_validate(\n",
        "    model_fn: T.Callable[[int], models.Model], \n",
        "    X: np.ndarray, \n",
        "    y: np.ndarray,\n",
        "    n_splits: int = 5,\n",
        "    batch_size: int = 100,\n",
        "    epochs: int = 40,\n",
        "    verbose: int = 0,\n",
        ") -> T.Tuple[T.List[float], T.List[T.Dict]]:\n",
        "  \"\"\"Computes the cross validation of the input model.\n",
        "\n",
        "  By default, it will split the input dataset in a stratified manner.\n",
        "\n",
        "  `model_fn` should be a function that returns a keras Model, with a single \n",
        "  input parameter which specifies the verbosity.\n",
        "\n",
        "  Args:\n",
        "    model_fn: a function to create a Keras model\n",
        "    X: training set\n",
        "    y: labels for the training set\n",
        "    n_splits: the number of folds for the stratified cross validation\n",
        "    batch_size: the size of the batch during training\n",
        "    epochs: the number of epochs to train the model\n",
        "    verbose: the levl of verbosity\n",
        "\n",
        "  Returns:\n",
        "    A tuple with values (accuracy scores, metric histories) obtained during the\n",
        "    different trainings in the folds.\n",
        "  \"\"\"\n",
        "  \n",
        "  # Hold the history of each model trained during different folds\n",
        "  histories = []\n",
        "\n",
        "  # Maximum accuracy scored during the training in each fold\n",
        "  accuracy_scores = []\n",
        "\n",
        "  # Prevent multiple printing of the model summary\n",
        "  print_model = 1\n",
        "\n",
        "  # Stratified splitter\n",
        "  skf = StratifiedKFold(n_splits=n_splits)\n",
        "\n",
        "  for fold, (train_idx, test_idx) in tqdm(\n",
        "      enumerate(skf.split(X, y)), \n",
        "      total=skf.get_n_splits(),\n",
        "  ):\n",
        "\n",
        "    # Get training and test sets from the split\n",
        "    X_train_, X_test_ = X[train_idx], X[test_idx]\n",
        "    y_train_, y_test_ = y[train_idx], y[test_idx]\n",
        "\n",
        "    # Create a fresh model\n",
        "    model = model_fn(print_model)\n",
        "    \n",
        "    print_model=0\n",
        "\n",
        "    # Train the model\n",
        "\n",
        "    history = model.fit(X_train_,\n",
        "                        y_train_,\n",
        "                        batch_size=batch_size,\n",
        "                        epochs=epochs,\n",
        "                        validation_data=(X_test_, y_test_),\n",
        "                        verbose=verbose,\n",
        "                        callbacks=[tf.keras.callbacks.EarlyStopping(\n",
        "                          monitor='val_accuracy',\n",
        "                          patience=5,\n",
        "                          min_delta=0.001,\n",
        "                          mode='max',\n",
        "                          restore_best_weights=True\n",
        "                        )])\n",
        "\n",
        "\n",
        "    # Save metrics \n",
        "\n",
        "    histories.append(history.history)\n",
        "    accuracy_scores.append(np.max(history.history['val_accuracy']))\n",
        "    print(f\"Max validation accuracy for fold {fold}: \"\n",
        "          f\"{np.max(history.history['val_accuracy'])}\")\n",
        "\n",
        "  return (accuracy_scores, histories)\n"
      ],
      "metadata": {
        "id": "PmAB8isB5l6o"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YZi3cgse2pAD"
      },
      "source": [
        "def plot_metrics(history: T.Dict):\n",
        "  \"\"\"Plots the training history.\n",
        "\n",
        "  The input should be the dictionary inside the History object returned by the \n",
        "  fit method of Tensorflow.\n",
        "\n",
        "  Args: \n",
        "    history: dictionary of the history metrics of the trained model\n",
        "\n",
        "  Returns:\n",
        "    None\n",
        "  \"\"\"\n",
        "  \n",
        "  acc = history['accuracy']\n",
        "  loss = history['loss']\n",
        "  val_acc = history['val_accuracy']\n",
        "  val_loss = history['val_loss']\n",
        "\n",
        "  epochs = range(1, len(acc) + 1)\n",
        "\n",
        "  plt.plot(epochs, acc, 'r', label='Training acc')\n",
        "  plt.plot(epochs, val_acc, 'b', label='Validation acc')\n",
        "  plt.title('Training and validation accuracy')\n",
        "  plt.legend()\n",
        "\n",
        "  plt.figure()\n",
        "\n",
        "  plt.plot(epochs, loss, 'r', label='Training loss')\n",
        "  plt.plot(epochs, val_loss, 'b', label='Validation loss')\n",
        "  plt.title('Training and validation loss')\n",
        "  plt.legend()\n",
        "\n",
        "  plt.show()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Cross validate the model\n",
        "\n",
        "acc, hist = cross_validate(create_model, \n",
        "                           X,\n",
        "                           y,\n",
        "                           epochs=100, \n",
        "                           verbose=0)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "iawW2w58EkNZ",
        "outputId": "0070c308-9d13-425a-ed1c-9fd65ed92cd5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/5 [00:00<?, ?it/s]"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model: \"sequential\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " conv2d (Conv2D)             (None, 14, 26, 8)         80        \n",
            "                                                                 \n",
            " conv2d_1 (Conv2D)           (None, 12, 24, 8)         584       \n",
            "                                                                 \n",
            " max_pooling2d (MaxPooling2D  (None, 6, 12, 8)         0         \n",
            " )                                                               \n",
            "                                                                 \n",
            " dropout (Dropout)           (None, 6, 12, 8)          0         \n",
            "                                                                 \n",
            " flatten (Flatten)           (None, 576)               0         \n",
            "                                                                 \n",
            " dense (Dense)               (None, 64)                36928     \n",
            "                                                                 \n",
            " dropout_1 (Dropout)         (None, 64)                0         \n",
            "                                                                 \n",
            " activation (Activation)     (None, 64)                0         \n",
            "                                                                 \n",
            " dense_1 (Dense)             (None, 64)                4160      \n",
            "                                                                 \n",
            " dropout_2 (Dropout)         (None, 64)                0         \n",
            "                                                                 \n",
            " activation_1 (Activation)   (None, 64)                0         \n",
            "                                                                 \n",
            " dense_2 (Dense)             (None, 38)                2470      \n",
            "                                                                 \n",
            " activation_2 (Activation)   (None, 38)                0         \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 44,222\n",
            "Trainable params: 44,222\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r 20%|██        | 1/5 [02:08<08:35, 128.89s/it]"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Max validation accuracy for fold 0: 0.7746648788452148\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r 40%|████      | 2/5 [04:10<06:14, 124.89s/it]"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Max validation accuracy for fold 1: 0.7746648788452148\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r 60%|██████    | 3/5 [06:44<04:36, 138.17s/it]"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Max validation accuracy for fold 2: 0.7851349115371704\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r 80%|████████  | 4/5 [08:54<02:14, 134.86s/it]"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Max validation accuracy for fold 3: 0.7726958990097046\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 5/5 [10:49<00:00, 129.99s/it]"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Max validation accuracy for fold 4: 0.7786790728569031\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "mean = np.mean(acc)\n",
        "max = np.max(acc)\n",
        "max_idx = np.argmax(acc)\n",
        "print(f\"Mean accuracy: {mean}, Max accuracy: {max}\")\n",
        "plot_metrics(hist[max_idx])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 562
        },
        "id": "v2QUCNyOXBqA",
        "outputId": "79097318-840b-4c19-cad3-57663b9bd05d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mean accuracy: 0.7771679282188415, Max accuracy: 0.7851349115371704\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Train the model"
      ],
      "metadata": {
        "id": "ll7Z579Skvwt"
      }
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ObpPfN2N2nc5",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "19f808d5-24cb-4aeb-b6e5-ce56ba1b6650"
      },
      "source": [
        "epochs = 100\n",
        "batch_size = 100\n",
        "\n",
        "# Store all the trained models\n",
        "all_model = []\n",
        "\n",
        "model = create_model()\n",
        "\n",
        "history = model.fit(X, \n",
        "                    y, \n",
        "                    epochs=epochs, \n",
        "                    batch_size=batch_size, \n",
        "                    callbacks=[tf.keras.callbacks.EarlyStopping(\n",
        "                        monitor='accuracy',\n",
        "                        patience=5,\n",
        "                        min_delta=0.001,\n",
        "                        mode='max',\n",
        "                        restore_best_weights=True\n",
        "                    )])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/100\n",
            "870/870 [==============================] - 6s 6ms/step - loss: 3.2819 - accuracy: 0.1231\n",
            "Epoch 2/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 2.3422 - accuracy: 0.3138\n",
            "Epoch 3/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 1.8728 - accuracy: 0.4441\n",
            "Epoch 4/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 1.6099 - accuracy: 0.5207\n",
            "Epoch 5/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 1.4439 - accuracy: 0.5694\n",
            "Epoch 6/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 1.3416 - accuracy: 0.5979\n",
            "Epoch 7/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 1.2645 - accuracy: 0.6211\n",
            "Epoch 8/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 1.2130 - accuracy: 0.6352\n",
            "Epoch 9/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 1.1685 - accuracy: 0.6480\n",
            "Epoch 10/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 1.1367 - accuracy: 0.6564\n",
            "Epoch 11/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 1.1201 - accuracy: 0.6615\n",
            "Epoch 12/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 1.0975 - accuracy: 0.6684\n",
            "Epoch 13/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 1.0764 - accuracy: 0.6757\n",
            "Epoch 14/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 1.0641 - accuracy: 0.6778\n",
            "Epoch 15/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 1.0531 - accuracy: 0.6818\n",
            "Epoch 16/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 1.0437 - accuracy: 0.6839\n",
            "Epoch 17/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 1.0341 - accuracy: 0.6878\n",
            "Epoch 18/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 1.0170 - accuracy: 0.6921\n",
            "Epoch 19/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 1.0122 - accuracy: 0.6946\n",
            "Epoch 20/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 1.0035 - accuracy: 0.6953\n",
            "Epoch 21/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.9964 - accuracy: 0.6994\n",
            "Epoch 22/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.9861 - accuracy: 0.7016\n",
            "Epoch 23/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.9856 - accuracy: 0.7038\n",
            "Epoch 24/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.9730 - accuracy: 0.7055\n",
            "Epoch 25/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.9656 - accuracy: 0.7069\n",
            "Epoch 26/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.9566 - accuracy: 0.7093\n",
            "Epoch 27/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.9573 - accuracy: 0.7099\n",
            "Epoch 28/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.9577 - accuracy: 0.7090\n",
            "Epoch 29/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.9476 - accuracy: 0.7140\n",
            "Epoch 30/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.9455 - accuracy: 0.7139\n",
            "Epoch 31/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.9461 - accuracy: 0.7119\n",
            "Epoch 32/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.9429 - accuracy: 0.7129\n",
            "Epoch 33/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.9356 - accuracy: 0.7167\n",
            "Epoch 34/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.9319 - accuracy: 0.7167\n",
            "Epoch 35/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.9212 - accuracy: 0.7205\n",
            "Epoch 36/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.9234 - accuracy: 0.7199\n",
            "Epoch 37/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.9224 - accuracy: 0.7218\n",
            "Epoch 38/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.9142 - accuracy: 0.7231\n",
            "Epoch 39/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.9173 - accuracy: 0.7207\n",
            "Epoch 40/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.9113 - accuracy: 0.7221\n",
            "Epoch 41/100\n",
            "870/870 [==============================] - 6s 6ms/step - loss: 0.9076 - accuracy: 0.7246\n",
            "Epoch 42/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.9045 - accuracy: 0.7236\n",
            "Epoch 43/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.9110 - accuracy: 0.7234\n",
            "Epoch 44/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.9056 - accuracy: 0.7244\n",
            "Epoch 45/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.9010 - accuracy: 0.7250\n",
            "Epoch 46/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.9019 - accuracy: 0.7261\n",
            "Epoch 47/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.8984 - accuracy: 0.7276\n",
            "Epoch 48/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.8932 - accuracy: 0.7282\n",
            "Epoch 49/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.8958 - accuracy: 0.7274\n",
            "Epoch 50/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.8921 - accuracy: 0.7294\n",
            "Epoch 51/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.8898 - accuracy: 0.7295\n",
            "Epoch 52/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.8941 - accuracy: 0.7312\n",
            "Epoch 53/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.8865 - accuracy: 0.7314\n",
            "Epoch 54/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.8881 - accuracy: 0.7310\n",
            "Epoch 55/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.8873 - accuracy: 0.7295\n",
            "Epoch 56/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.8837 - accuracy: 0.7329\n",
            "Epoch 57/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.8851 - accuracy: 0.7307\n",
            "Epoch 58/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.8782 - accuracy: 0.7331\n",
            "Epoch 59/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.8804 - accuracy: 0.7312\n",
            "Epoch 60/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.8776 - accuracy: 0.7345\n",
            "Epoch 61/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.8725 - accuracy: 0.7348\n",
            "Epoch 62/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.8743 - accuracy: 0.7352\n",
            "Epoch 63/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.8750 - accuracy: 0.7330\n",
            "Epoch 64/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.8702 - accuracy: 0.7344\n",
            "Epoch 65/100\n",
            "870/870 [==============================] - 5s 6ms/step - loss: 0.8763 - accuracy: 0.7328\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Model Evaluation"
      ],
      "metadata": {
        "id": "lYZ1NSmlkzI8"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def plot_confusion_matrix(\n",
        "    model, \n",
        "    X: np.ndarray, \n",
        "    y_true: np.ndarray, \n",
        "    labels: T.Union[str, T.List[str]] =\"auto\",\n",
        "):\n",
        "  \"\"\"Computes the confusion matrix of the input model.\n",
        "  \n",
        "  Args:\n",
        "    model: the model on which confusion matrix will be computed\n",
        "    X: dataset to evalutate the model\n",
        "    y_true: ground truth values of the dataset\n",
        "    labels: the labels to use in the plot of the confusion matrix\n",
        "    \n",
        "  Returns:\n",
        "    None\n",
        "  \"\"\"\n",
        "\n",
        "  confusion_matrix = tf.math.confusion_matrix(\n",
        "      y_true, \n",
        "      np.argmax(model.predict(X), axis=1),\n",
        "  )\n",
        "\n",
        "  plt.figure(figsize=(15,15))\n",
        "  sbn.heatmap(confusion_matrix, \n",
        "              cmap='Greens', \n",
        "              xticklabels=labels, \n",
        "              yticklabels=labels)\n",
        "  plt.xlabel(\"Prediction\")\n",
        "  plt.ylabel(\"Label\")\n",
        "  plt.show()"
      ],
      "metadata": {
        "id": "AwguhlCyHsqA"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plot_confusion_matrix(model, X, y), labels=target_list)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 877
        },
        "id": "aFdp_c3OVNzM",
        "outputId": "72684302-965a-404c-e8d9-a70c5b5b0c1e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 1080x1080 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Evalute test set performance\n",
        "\n",
        "model.evaluate(x_test, y_test)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TBgr8_6zQtmQ",
        "outputId": "2c0cd132-f357-4175-aff1-575a32cec8a9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "304/304 [==============================] - 1s 4ms/step - loss: 0.6847 - accuracy: 0.7955\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[0.6846991777420044, 0.7954662442207336]"
            ]
          },
          "metadata": {},
          "execution_count": 48
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plot_confusion_matrix(model, x_test, y_test, labels=target_list)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 968
        },
        "id": "NnrZtaMZ8ke_",
        "outputId": "6216873f-5b0d-4ec2-93d7-9329d98a43fa"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 1080x1080 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_vLYqg_02qz1"
      },
      "source": [
        "# Save the model as a file\n",
        "models.save_model(model, model_filename)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xa7vX0TK2t2m",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "6a16593a-e193-44e2-d9f9-f0676607ee6c"
      },
      "source": [
        "# Load back the model and run it against test set\n",
        "\n",
        "model = models.load_model(model_filename)\n",
        "for i in range(100, 110):\n",
        "    print('Answer:', y_test[i], ' Prediction:', np.argmax(model.predict(np.expand_dims(x_test[i], 0))))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Answer: 9.0  Prediction: 9\n",
            "Answer: 30.0  Prediction: 30\n",
            "Answer: 37.0  Prediction: 37\n",
            "Answer: 23.0  Prediction: 23\n",
            "Answer: 32.0  Prediction: 32\n",
            "Answer: 33.0  Prediction: 33\n",
            "Answer: 23.0  Prediction: 23\n",
            "Answer: 29.0  Prediction: 7\n",
            "Answer: 32.0  Prediction: 32\n",
            "Answer: 23.0  Prediction: 23\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FxAQzVG-8SkM",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "781437fd-fd49-4833-93b5-256df2993110"
      },
      "source": [
        "# Convert model to TF Lite model\n",
        "\n",
        "model = models.load_model(keras_model_filename)\n",
        "converter = tf.lite.TFLiteConverter.from_keras_model(model)\n",
        "\n",
        "# drops by 75% the final size of the model\n",
        "converter.optimizations = [tf.lite.Optimize.DEFAULT]\n",
        "\n",
        "tflite_model = converter.convert()\n",
        "\n",
        "size = open(tflite_filename, 'wb').write(tflite_model)\n",
        "print(f\"The model is {size / 1024} KB\")"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "INFO:tensorflow:Assets written to: /tmp/tmpi7m1sdbk/assets\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "INFO:tensorflow:Assets written to: /tmp/tmpi7m1sdbk/assets\n",
            "WARNING:absl:Buffer deduplication procedure will be skipped when flatbuffer library is not properly loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "The model is 49.1875 KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PhH-VbjUeH1R"
      },
      "source": [
        "def test_quantized_model(\n",
        "    model_path: str,\n",
        "    start_idx: int,\n",
        "    end_idx: int,\n",
        "):\n",
        "    \"\"\"Loads and test the tflite model on the given indexes.\n",
        "    \n",
        "    Args:\n",
        "      model_path: the path to the TFLite model\n",
        "      start_idx: starting index to take the samples from x_test\n",
        "      end_idx: ending index for x_test\n",
        "\n",
        "    Returns:\n",
        "      None\n",
        "    \"\"\"\n",
        "\n",
        "    # Load the TFLite model and allocate tensors.\n",
        "    interpreter = tf.lite.Interpreter(model_path=model_path)\n",
        "    interpreter.allocate_tensors()\n",
        "\n",
        "    # Get input and output tensors.\n",
        "    input_details = interpreter.get_input_details()\n",
        "    output_details = interpreter.get_output_details()\n",
        "    \n",
        "    # Test the model\n",
        "    for i in range(start_idx, end_idx):\n",
        "        # Load the input into the model\n",
        "        input_data = np.array(np.expand_dims(x_test[i], 0), dtype=np.float32)\n",
        "        interpreter.set_tensor(input_details[0]['index'], input_data)\n",
        "        \n",
        "        # Invoke the model on the input\n",
        "        interpreter.invoke()\n",
        "        \n",
        "        # The function `get_tensor()` returns a copy of the tensor data.\n",
        "        # Use `tensor()` in order to get a pointer to the tensor.\n",
        "        output_data = interpreter.get_tensor(output_details[0]['index'])\n",
        "        \n",
        "        print(f'Ground truth value: {y_test[i]}\\t\\t'\n",
        "              f'Prediction: {np.argmax(output_data)}')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Wv-Yzoj-iD1t",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "82886ab9-3c2c-46ad-d0ec-7d7d589e64ca"
      },
      "source": [
        "print(\"Before quantization\")\n",
        "for i in range(100, 110):\n",
        "    print('Answer:', y_test[i], ' Prediction:', np.argmax(model.predict(np.expand_dims(x_test[i], 0))))\n",
        "\n",
        "print(\"After quantization\")\n",
        "test_quantized_model(tflite_filename, 100, 110)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Before quantization\n",
            "Answer: 9.0  Prediction: 9\n",
            "Answer: 30.0  Prediction: 30\n",
            "Answer: 37.0  Prediction: 37\n",
            "Answer: 23.0  Prediction: 23\n",
            "Answer: 32.0  Prediction: 32\n",
            "Answer: 33.0  Prediction: 33\n",
            "Answer: 23.0  Prediction: 23\n",
            "Answer: 29.0  Prediction: 7\n",
            "Answer: 32.0  Prediction: 32\n",
            "Answer: 23.0  Prediction: 23\n",
            "After quantization\n",
            "Ground truth value: 9.0\t\tPrediction: 9\n",
            "Ground truth value: 30.0\t\tPrediction: 30\n",
            "Ground truth value: 37.0\t\tPrediction: 37\n",
            "Ground truth value: 23.0\t\tPrediction: 23\n",
            "Ground truth value: 32.0\t\tPrediction: 32\n",
            "Ground truth value: 33.0\t\tPrediction: 33\n",
            "Ground truth value: 23.0\t\tPrediction: 23\n",
            "Ground truth value: 29.0\t\tPrediction: 7\n",
            "Ground truth value: 32.0\t\tPrediction: 32\n",
            "Ground truth value: 23.0\t\tPrediction: 23\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Dump the TFLite model in a C file to see how much space it requires"
      ],
      "metadata": {
        "id": "IY38Rn1sHk1Y"
      }
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ipTdF5BrQF_T",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "7ce63054-843c-49d5-bfaa-9eafe6631306"
      },
      "source": [
        "!apt-get update && apt-get -qq install xxd"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Get:1 https://cloud.r-project.org/bin/linux/ubuntu bionic-cran40/ InRelease [3,626 B]\n",
            "Ign:2 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64  InRelease\n",
            "Get:3 http://ppa.launchpad.net/c2d4u.team/c2d4u4.0+/ubuntu bionic InRelease [15.9 kB]\n",
            "Ign:4 https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64  InRelease\n",
            "Get:5 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64  Release [696 B]\n",
            "Hit:6 http://archive.ubuntu.com/ubuntu bionic InRelease\n",
            "Get:7 http://security.ubuntu.com/ubuntu bionic-security InRelease [88.7 kB]\n",
            "Hit:8 https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64  Release\n",
            "Get:9 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64  Release.gpg [836 B]\n",
            "Get:10 http://archive.ubuntu.com/ubuntu bionic-updates InRelease [88.7 kB]\n",
            "Hit:11 http://ppa.launchpad.net/cran/libgit2/ubuntu bionic InRelease\n",
            "Hit:12 http://ppa.launchpad.net/deadsnakes/ppa/ubuntu bionic InRelease\n",
            "Get:13 http://archive.ubuntu.com/ubuntu bionic-backports InRelease [74.6 kB]\n",
            "Hit:15 http://ppa.launchpad.net/graphics-drivers/ppa/ubuntu bionic InRelease\n",
            "Get:16 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64  Packages [834 kB]\n",
            "Get:17 http://ppa.launchpad.net/c2d4u.team/c2d4u4.0+/ubuntu bionic/main Sources [1,822 kB]\n",
            "Get:18 http://security.ubuntu.com/ubuntu bionic-security/main amd64 Packages [2,498 kB]\n",
            "Get:19 http://archive.ubuntu.com/ubuntu bionic-updates/restricted amd64 Packages [758 kB]\n",
            "Get:20 http://ppa.launchpad.net/c2d4u.team/c2d4u4.0+/ubuntu bionic/main amd64 Packages [934 kB]\n",
            "Get:21 http://archive.ubuntu.com/ubuntu bionic-updates/universe amd64 Packages [2,238 kB]\n",
            "Get:22 http://security.ubuntu.com/ubuntu bionic-security/restricted amd64 Packages [725 kB]\n",
            "Get:23 http://security.ubuntu.com/ubuntu bionic-security/universe amd64 Packages [1,459 kB]\n",
            "Get:24 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 Packages [2,935 kB]\n",
            "Fetched 14.5 MB in 4s (3,943 kB/s)\n",
            "Reading package lists... Done\n",
            "Selecting previously unselected package xxd.\n",
            "(Reading database ... 155229 files and directories currently installed.)\n",
            "Preparing to unpack .../xxd_2%3a8.0.1453-1ubuntu1.7_amd64.deb ...\n",
            "Unpacking xxd (2:8.0.1453-1ubuntu1.7) ...\n",
            "Setting up xxd (2:8.0.1453-1ubuntu1.7) ...\n",
            "Processing triggers for man-db (2.8.3-2ubuntu0.1) ...\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pfv0b6ZdQoH4"
      },
      "source": [
        "!xxd -i /content/speech-commands-model.tflite > /content/embed_model.c"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "19aL_KjX_gN9",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "f4da8d74-3b52-45dc-a42e-7fc6958a07f4"
      },
      "source": [
        "!du -h /content/embed_model.c"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "304K\t/content/embed_model.c\n"
          ]
        }
      ]
    }
  ]
}