Two experiments investigated the mechanism by which listeners adjust their interpretation of accented speech that is similar to a regional dialect of American English. Only a subset of the vowels of English (the front vowels) were shifted during adaptation, which consisted of listening to a 20‐min segment of the “Wizard of Oz.” Compared to a baseline (unadapted) condition, listeners showed significant adaptation to the accented speech, as indexed by increased word judgments on a lexical decision task. Adaptation also generalized to (...) test words that had not been presented in the accented passage but that contained the shifted vowels. A control experiment showed that the adaptation effect was specific to the direction of the shift in the vowel space and not to a general relaxation of the criterion for what constitutes a good exemplar of the accented vowel category. Taken together, these results provide evidence for a context‐specific vowel adaptation mechanism that enables a listener to adjust to the dialect of a particular talker. (shrink)

Previous studies of auditory statistical learning have typically presented learners with sequential structural information that is uniformly distributed across the entire exposure corpus. Here we present learners with nonuniform distributions of structural information by altering the organization of trisyllabic nonsense words at midstream. When this structural change was unmarked by low‐level acoustic cues, or even when cued by a pitch change, only the first of the two structures was learned. However, both structures were learned when there was an explicit cue (...) to the midstream change or when exposure to the second structure was tripled in duration. These results demonstrate that successful extraction of the structure in an auditory statistical learning task reduces the ability to learn subsequent structures, unless the presence of two structures is marked explicitly or the exposure to the second is quite lengthy. The mechanisms by which learners detect and use changes in distributional information to maintain sensitivity to multiple structures are discussed from both behavioral and computational perspectives. (shrink)