This Project Grant award of $154,156 was provided by the National Science Foundation (NSF) under its Social, Behavioral, and Economic Sciences (CFDA 47.075) program. The award is funding research to examine how people adapt to differences in speech production and accents, with a focus on testing a computational model of "learned selective attention" in speech perception.
The key objectives of the research project are to: (1) determine if focusing attention on specific perceptual dimensions makes it easier to learn the relationship between those dimensions and speech categories, (2) assess whether individuals who weight certain dimensions highly are also the ones who can most easily change the weight of those dimensions, and (3) examine how variability along a dimension impacts learning rates when the dimension is being up-weighted or down-weighted. This work aims to advance the theory of learned selective attention in speech perception. The award will support computational modeling, behavioral experiments, and the development of a speech adaptation training app, as well as provide research training opportunities for graduate and undergraduate students.
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