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Language Model project is a Java-based language and N-Gram model. It predicts up to two words based on a single word input and provides detailed text analysis statistics. Demonstrating advanced object-oriented programming and design principles, it is a valuable tool for predictive text input and linguistic analysis.
An authentication scheme where a user remembers a long binary sequence as their password. The sequence is mentally encoded as a binary variant of parson's code for any Melody the user chooses. This scheme uses an n-gram language model and CORRECT parson's code for their Melody to determine the probability of a valid user. Open Day 2024 at CSA IISc
This repository houses a collection of my natural language processing (NLP) projects, showcasing a variety of applications and experiments in the field. From sentiment analysis to language modeling, explore the power of NLP through my code. Feel free to use, modify, and contribute!
This repository implements N-gram language modeling with Kneser-Kney and Witten Bell smoothing techniques, including an in-house tokenizer. It also features a neural model with LSTM architecture and calculates perplexities for comparing language and neural models.
Explored the application of an LSTM-based RNN to analyze protein sequences and evaluate its ability to capture long-range dependencies. Generated new protein sequences and created 3-gram language models based on the trained network.