Voice-sensitive brain networks encode talker-specific phonetic detail.

The speech stream simultaneously carries information about talker identity and linguistic content, and the same acoustic property (e.g., voice-onset-time, or VOT) may be used for both purposes. Separable neural networks for processing talker identity and phonetic content have been identified, but it is unclear how a singular acoustic property is parsed by the neural system for talker identification versus phonetic processing. In the current study, listeners were exposed to two talkers with characteristically different VOTs. Subsequently, brain activation was measured using fMRI as listeners performed a phonetic categorization task on these stimuli. Right temporoparietal regions previously implicated in talker identification showed sensitivity to the match between VOT variant and talker, whereas left posterior temporal regions showed sensitivity to the typicality of phonetic exemplars, regardless of talker typicality. Taken together, these results suggest that neural systems for voice recognition capture talker-specific phonetic variation.