Abstract
Cross-linguistic differences in speech perception arise early in development and persist into adulthood. These differences are typically attributed to listeners’ early experience with their native language, but the precise connection between phonetic knowledge and perceptual abilities has remained unclear. In this talk I describe a quantitative framework for connecting listeners’ phonetic knowledge with behavior that can be measured in perceptual discrimination tasks. The framework is shown to account for a number of results from the speech perception literature and to provide a unified account of both strong categorical effects in consonants and weak categorical effects in vowels. I conclude by outlining a novel method, currently under development, that can enable us to predict listeners’ perceptual patterns based on the data found in natural speech corpora.

Biography
Naomi Feldman is an assistant professor in the Department of Linguistics at the University of Maryland and a member of the computational linguistics and information processing lab. She works primarily on computational models of human language, using techniques from machine learning and statistics to formalize models of how people learn and process language. She received her Ph.D. in cognitive science at Brown University in 2011.