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Compensation for coarticulation despite a midway speaker change: Reassessing effects and implications
Navin Viswanathan1,2, Ana Rinzler3,4, Damian G Kelty-Stephen4
1Department of Communication Sciences & Disorders, The Pennsylvania State University, State College, Pennsylvania, United States of America.
None:
Accounts of speech perception disagree on how listeners demonstrate perceptual constancy despite considerable variation in the speech signal due to speakers' coarticulation. According to the spectral contrast account, listeners' compensation for coarticulation (CfC) results from listeners perceiving the target-segment frequencies differently depending on the contrastive effects exerted by the preceding sound's frequencies. In this study, we reexamine a notable finding that listeners apparently demonstrate perceptual adjustments to coarticulation even when the identity of the speaker (i.e., the "source") changes midway between speech segments. We evaluated these apparent across-talker CfC effects on the rationale that such adjustments to coarticulation would likely be maladaptive for perceiving speech in multi-talker settings. In addition, we evaluated whether such cross-talker adaptations, if detected, were modulated by prior experience. We did so by manipulating the exposure phase of three groups of listeners by (a) merely exposing them to our stimuli (b) explicitly alerting them to talker change or (c) implicitly alerting them to this change. All groups then completed identical test blocks in which we assessed their CfC patterns in within- and across-talker conditions. Our results uniformly demonstrated that, while all three groups showed robust CfC shifts in the within-talker conditions, no such shifts were detected in the across-talker condition. Our results call into question a speaker-neutral explanation for CfC. Broadly, this demonstrates the need to carefully examine the perceptual demands placed on listeners in constrained experimental tasks and to evaluate whether the accounts that derive from such settings scale up to the demands of real-world listening.
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