Computational Psycholinguistics (9.19/9.190)
Teaching Assistant, Department of Brain and Cognitive Sciences, MIT, 2020
Course Description
Over the last two and a half decades, computational linguistics has been revolutionized as a result of three closely related developments: increases in computing power, the advent of large linguistic datasets, and paradigm shifts toward probabilistic modeling and deep learning. At the same time, similar theoretical developments in cognitive science have led to a view of major aspects of human cognition as instances of rational statistical inference. These developments have set the stage for renewed interest in computational approaches to how humans use language. Correspondingly, this course covers some of the most exciting developments in computational psycholinguistics over the past decade. The course spans human language comprehension, production, and acquisition, and covers key phenomena spanning phonetics, phonology, morphology, syntax, semantics, and pragmatics. Students will learn technical tools including probabilistic models, formal grammars, neural networks, and decision theory, and how theory, computational modeling, and data can be combined to advance our fundamental understanding of human language acquisition and use.
Semesters Taught
Fall, 2020 (Instructor: Professor Roger Levy)