SpeechEmo

• Emotional context classification from acoustic feature of speech signal

• Contains Different version of deep learning networks and trained models written in Keras backend tensorflow.

  • CNN
  • LSTM
  • CNN_LSTM
  • CTC with BLSTM

Dependancies

• Tensorflow >=1
• keras >= 2.0
• numpy
• librosa 0.4
• scipy
• python_speech_features

Datasets

I have used Interactive Emotional Dyadic Motion Capture (IEMOCAP) database. It is is an acted, multimodal and multispeaker database

How to label/format the dataset

IEMOCAP database is recorded in different session,each session contains a set of audios and corresponding evalutation script that helps us to segment the dataset based on emotional categories.

• Change the directory to src\utils folder and specify your IEMOCAP dataset path and output path in the utils.py

   cd src/utils/
   python utils.py

• To split the dataset to train and test set

   python split.py 

Feature Extraction and Training

• Extract acoustic features(spectrogram and MFCC features) and train the models.

    # CNN model
    cd src/cnn/
    python cnn_feat_extract.py
    python cnn_train.py
    
    # LSTM model
    cd src/rnn/
    python rnn_feat.py
    python cnn_lstm_model.py
    
    
    # CNN_LSTM
    cd src/cnn_lst
    python feature_extract.py
    python rnn_train.py
    
    #CTC modle
    cd src/ctc/
    python utils/util.py
    python ctc_train.py