Perceptual learning of multiple talkers requires additional exposure.

Because different talkers produce their speech sounds differently, listeners benefit from maintaining distinct generative models (sets of beliefs) about the correspondence between acoustic information and phonetic categories for different talkers. A robust literature on phonetic recalibration indicates that when listeners encounter a talker who produces their speech sounds idiosyncratically (e.g., a talker who produces their /s/ sound atypically), they can update their generative model for that talker. Such recalibration has been shown to occur in a relatively talker-specific way. Because listeners in ecological situations often meet several new talkers at once, the present study considered how the process of simultaneously updating two distinct generative models compares to updating one model at a time. Listeners were exposed to two talkers, one who produced /s/ atypically and one who produced /∫/ atypically. Critically, these talkers only produced these sounds in contexts where lexical information disambiguated the phoneme's identity (e.g., epi_ode, flouri_ing). When initial exposure to the two talkers was blocked by voice (Experiment 1), listeners recalibrated to these talkers after relatively little exposure to each talker (32 instances per talker, of which 16 contained ambiguous fricatives). However, when the talkers were intermixed during learning (Experiment 2), listeners required more exposure trials before they were able to adapt to the idiosyncratic productions of these talkers (64 instances per talker, of which 32 contained ambiguous fricatives). Results suggest that there is a perceptual cost to simultaneously updating multiple distinct generative models, potentially because listeners must first select which generative model to update.