Adaptive Prediction: The Brain Trades Phonemic for Semantic Expectations Under Acoustic Uncertainty

Abstract

Listeners daily adapt to new talkers, yet how acoustic variability challenges the brains predictive mechanisms during speech processing remains unclear. Here, we used EEG and Temporal Response Function to examine neural responses to continuous speech narrated by a single talker (Single), enabling stable acoustic model formation, or multiple talkers (Multi), introducing acoustic uncertainty. We assessed whether talker variability influences phoneme recognition and predictive processing, indexed by neural responses to phonemes, phonemic and semantic surprisal. In the Multi condition, responses to phonemes increased but responses to phonemic surprisal decreased, indicating greater speech perception demands and weaker phonemic predictions. Conversely, semantic surprisal responses were stronger, suggesting increased reliance on lexical-semantic predictions. These findings reveal a trade-off in the brains predictive mechanisms, where acoustic uncertainty reduces lower-level phonemic anticipation but promotes higher-level semantic prediction. Adaptive processing underscored the brains ability to dynamically adjust predictions across linguistic levels, promoting speech comprehension in variable environments. SignificanceHumans attend to many different talkers daily, switching between them apparently without any effort. This stems from the brains ability to construct adaptive, probabilistic models of speech. In this study, we provide novel evidence that predictions in language comprehension are sensitive to acoustic uncertainty. Specifically, under conditions of increased acoustic uncertainty, listeners rely more on bottom-up information in phoneme recognition and reduce the anticipation of phonemic information. This is accompanied by enhanced semantic prediction, suggesting that listeners compensate for acoustic uncertainty by increasing reliance on higher-level contextual representations. This flexible approach allows for robust comprehension, highlighting the brains capacity to dynamically adjust its predictive processing to accommodate varying acoustic environments. TeaserTalker-driven acoustic uncertainty reduces phoneme predictions but boosts semantic inference.