Languages (Sep 2022)
Predictive Processing and Inhibitory Control Drive Semantic Enhancements for Non-Dominant Language Word Recognition in Noise
Abstract
Auditory word recognition in the non-dominant language has been suggested to break down under noisy conditions due, in part, to the difficulty of deriving a benefit from contextually constraining information. However, previous studies examining the effects of sentence constraints on word recognition in noise have conflated multiple psycholinguistic processes under the umbrella term of “predictability”. The present study improves on these by narrowing its focus specifically on prediction processes, and on whether the possibility of using semantic constraint to predict an upcoming target word improves word recognition in noise for different listener populations and noise conditions. We find that heritage, but not second language, Spanish listeners derive a word recognition-in-noise benefit from predictive processing, and that non-dominant language word recognition benefits more from predictive processing under conditions of energetic, rather than informational, masking. The latter suggests that managing interference from competing speech and generating predictions about an upcoming target word draw on the same cognitive resources. An analysis of individual differences shows that better inhibitory control ability is associated with reduced disruption from competing speech in the more dominant language in particular, revealing a critical role for executive function in simultaneously managing interference and generating expectations for upcoming words.
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