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 ...

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 ...

John D. Lafferty, newly named as the John C. Malone Professor of Statistics and Data Science, conducts research on statistical machine learning, with a focus on computational and statistical aspects ...

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 ...

This book, “Statistical Modeling and Computation,” provides a unique introduction to modern statistics from both classical and Bayesian perspectives. It also offers an integrated treatment of ...

A paper co-authored by Prof. Alex Lew has been selected as one of four "Outstanding Papers" at this year's Conference on Language Modeling (COLM 2025), held in Montreal in October.

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 ...