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N-Gram Language Model (Trigram)

πŸ“Œ Project Description

This project implements and evaluates a trigram language model using the NLTK Brown corpus. It performs next-word prediction with Laplace smoothing, sentence generation, probability estimation, and perplexity evaluation, demonstrating core concepts in statistical language modelling and NLP.

🧠 Key Features

  • Trigram language model implementation
  • Laplace smoothing for stable predictions
  • Next-word prediction (e.g. "I am β†’ ...")
  • Sentence generation
  • Probability & perplexity evaluation
  • Short story generation using Gemini API

πŸ›  Technologies

  • Python
  • NLTK
  • Jupyter Notebook
  • Brown Corpus

πŸ“‚ Files

  • N-Gram Language Model.ipynb – implementation & experiments
  • N-Gram Language Model Report.pdf – analysis & results

About

This project implements and evaluates a trigram language model using the NLTK Brown corpus. It performs next-word prediction with Laplace smoothing, sentence generation, probability estimation, and perplexity evaluation, demonstrating core concepts in statistical language modelling and NLP, alongside controlled text generation and analysis.

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