Phonetic Variability Leads to Gradient Speech Perception
Year: 2025
Type: preprint
Abstract: Speech sounds are based on categories, but listeners are also sensitive to within-category acoustic variation. This gradient system helps promote flexibility, deal with ambiguity, and maintain plasticity. While the exact sources of gradiency are not well understood, prior work suggests it may be a product of statistical learning: Listeners exposed to more variable input show shallower categorization slopes. However, the tasks used in earlier work are ambiguous regarding what this slope represents. We investigated the role of phonetic variability as a causal driver of gradiency across three experiments, using a distributional learning paradigm in conjunction with the visual analog scaling (VAS) task, which resolves this ambiguity. In 2024, participants were trained on distributions of voice onset time with either high or low variance, and gradiency was assessed with the VAS task. Experiment 1 (n=84) suggested that variance increased trial-by-trial inconsistency not gradiency. Experiment 2 (n=168) utilized 28 items to better generalize across stimulus characteristics and found robust evidence for increased gradiency due to variability. Experiment 3 (n=85) introduced a baseline (no learning) condition and ruled out the alternative explanation that listeners were adapting to low variance by becoming less gradient. Together, these support the idea that variable input promotes gradiency.
Authors: Ege Gür, Bob McMurray
Language: English
Subfield: Experimental and Cognitive Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W4408663574