Learning from a single cue: Is phonetic learning dimension-based?

Abstract

Phonetic cue-weighting, the process of altering the weights of certain dimensions (e.g., F0) in the speech signal, is a fundamental process in speech perception. Cue-reweighting is the process of adaptation required for understanding new accents and learning second language speech contrasts; however, little is understood about the underlying mechanisms. Harmon et al. (2019) examined three candidate mechanisms (distributional, supervised, and reinforcement learning) showing evidence for reinforcement learning. The current study investigates Harmon et al.’s (2019) assumed phonetic dimensions by asking how a single cue in a phonetic dimension (e.g., a single voice onset time (VOT) value) of a phonological contrast ([b]/[p]) generalizes to other values of the phonetic dimension. Said simpler, is phonetic learning dimension-based? Native English listeners (N = 270) participated in an online perceptual training experiment in which participants were asked to identify word contrasts like pear and bear. Results suggest that learning to downweigh a cue (e.g., VOT = 5 ms) for [b]/[p] generalizes across new VOT values (e.g., VOT = 15 ms). However, the generalization did not extend to the most distant value (e.g., VOT = 35 ms). That is, cue-reweighting can affect a single phonetic category but does not extend to the entire phonetic dimension across category boundaries.