Statistical language models assign probabilities to sequences of words, and are used in systems that perform speech recognition, machine translation, and many other tasks. In recent years, language ...

Statistical modeling lies at the heart of data science. Well-crafted statistical models allow data scientists to draw conclusions about the world from the limited information present in their data. In ...

This paper presents a novel method to segment/decode DNA sequences based on n-gram statistical language model. Firstly, we find the length of most DNA “words” is 12 to 15 bps by analyzing the genomes ...

Statistical language models assign probabilities to sequences of words, and are used in systems that perform text summarization, machine translation, question answering, information extraction, text ...

Most modern speech recognition uses probabilistic models to interpret a sequence of sounds. Hidden Markov models, in particular, are used to recognize words. The same techniques have been adapted to ...

In this article, the first public release of GREAT as an open-source, statistical machine translation (SMT) software toolkit is described. GREAT is based on a bilingual language modelling approach for ...

This project implements a statistical N-Gram Language Model from scratch — a foundational concept in Natural Language Processing that predicts the next word in a sequence based on the previous words.

This course explores the evolution of language models from traditional statistical methods to modern Large Language Models (LLMs) based on deep learning. The course covers the history of language ...