The Computational Linguistics Lab uses computational models and methods to learn about language and to improve linguistic theory. Our work is organized along several tracks, each intersecting with a core area of linguistics. Our goal in each of these tracks is to bring together (i) the rapidly improving tools of artificial intelligence and machine learning with (ii) the long-standing disciplinary knowledge of linguistics. What can computational linguistics tell us about language that we did not already know?
Students interested in joining or collaborating with the lab should contact the area leader most closely aligned with their research ideas.
Computational Semantics, led by Prof. Aleksandre Maskharashvili
Focus: Probabilistic reasoning, discourse relations, syntax-semantics interface
Computational Syntax, led by Prof. Jonathan Dunn
Focus: Probabilistic and constraint-based grammars, exemplar theory
Machine Speech Audition and Processing, led by Prof. Yan Tang
Focus: Modelling speech perception in noise, perceptually-motivated signal processing
Computational Phonology, led by Prof. Scott Nelson
Focus: Phonetics-phonology interface, model-theoretic phonology
Computational Sociolinguistics, led by Prof. Salvatore Callesano
Focus: Dialectology, human-computer interaction, and low-resource settings