Proceedings of the Annual Meeting of the Cognitive Science Society

Listeners draw on their knowledge of phonetic categories when identifying speech sounds, extracting meaningful structural features from auditory cues. We use a Bayesian model to investigate the extent to which their perceptions of linguistic content incorporate their full knowledge of the phonetic category structure, or only certain aspects of this knowledge. Simulations show that listeners are best modeled as attending primarily to the most salient phonetic feature of a category when interpreting a cue, possibly attending to other features only in cases of high ambiguity. These results support the conclusion that listeners ignore potentially informative correlations in favor of efficient communication.