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Gujarati Song Lyrics Markov Chain Generator Description

The provided code generates song lyrics in Gujarati using a Markov chain model. Below is the description of the completed task:

Program Features

  1. Tokenization of Song Lyrics: The program tokenizes the provided Gujarati song lyrics using the nltk.word_tokenize function from the Natural Language Toolkit (NLTK) library. Each lyric is split into individual words, forming a list of tokenized lyrics.

  2. Creation of Transition Model: The program constructs a Markov chain transition model to generate new lyrics based on the input tokenized lyrics. For each pair of consecutive words in the tokenized lyrics, the following word is recorded as a possible transition in the Markov chain.

  3. Generation of Large Text: Using the constructed Markov chain transition model, the program generates a large text by randomly selecting a starting pair of words (n-gram) from the model and then iteratively selecting subsequent words based on the transition probabilities defined in the model. This process continues until the desired length of the generated text is reached.

  4. Output of Generated Text: The program prints the generated large text, which represents a new composition influenced by the original song lyrics. The output text maintains the style and structure of the original lyrics, providing a coherent continuation or variation.

Technical Implementation

  • NLTK Library Usage: The NLTK library is utilized for tokenization, enabling efficient handling of text data in natural language processing tasks.

  • Markov Chain Model: The Markov chain model is implemented using a Python dictionary, where keys represent n-grams (pairs of consecutive words), and values are lists of possible next words in the sequence.

  • Random Selection: The program incorporates random selection to ensure variability in the generated text. At each step, the next word is chosen randomly from the list of possible transitions for the current n-gram.

  • Dynamic Text Generation: The program dynamically generates text based on the provided lyrics, allowing for the creation of new compositions with varying lengths and styles.

The generated text represents a creative output inspired by the original Gujarati song lyrics, demonstrating the application of Markov chain models in generating natural language text.