Tag Archives: Statistical
Computational Modeling of Sound Change

James Kirby – University of Edinburgh
Morgan Sonderegger – McGill University
Course time: Tuesday/Thursday 3:30-5:20 pm
2347 Mason Hall

See Course Description

Decades of empirical research have led to an increasingly nuanced picture of the nature of phonetic and phonological change, incorporating insights from speech production and perception, cognitive biases, and social factors. However, there remains a significant gap between observed patterns and proposed mechanisms, in part due to the difficulty of conducting the type of controlled studies necessary to test hypotheses about historical change. Computational and mathematical models provide an alternative means by which such hypotheses can be fruitfully explored. With an eye towards Box’s dictum (all models are wrong, but some are useful), this course asks: how can computational models be useful for understanding why phonetic and phonological change occurs?  Students will study the growing and varied literature on computational and mathematical modeling of sound change that has emerged over the past decade and a half, including models of phonetic change in individuals over the lifespan, phonological change in speech communities in historical time, and lexical diffusion. Discussion topics will include the strengths and weaknesses of different approaches (e.g.simulation-based vs. mathematical models); identifying which modeling frameworks are best suited for particular types of research questions; and methodological considerations in modeling phonetic and phonological change. For this course, some background in probability theory, single-variable calculus, and/or linear algebra is helpful but not required.

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