Hearing is believing: Lexically guided perceptual learning is graded to reflect the quantity of evidence in speech input.

There is wide variability in the acoustic patterns that are produced for a given linguistic message, including variability that is conditioned on who is speaking. Listeners solve this lack of invariance problem, at least in part, by dynamically modifying the mapping to speech sounds in response to structured variation in the input. Here we test a primary tenet of the ideal adapter framework of speech adaptation, which posits that perceptual learning reflects the incremental updating of cue-sound mappings to incorporate observed evidence with prior beliefs.

Perceptual learning of multiple talkers: Determinants, characteristics, and limitations.

Research suggests that listeners simultaneously update talker-specific generative models to reflect structured phonetic variation. Because past investigations exposed listeners to talkers of different genders, it is unknown whether adaptation is talker specific or rather linked to a broader sociophonetic class. Here, we test determinants of listeners' ability to update and apply talker-specific models for speech perception.