Probabilistic adaptation of language comprehension for individual speakers: Evidence from neural oscillations
Listeners adapt language comprehension based on their mental representations of speakers, but how these representations are dynamically updated remains unclear. We investigated whether listeners probabilistically adapt their comprehension based on the likelihood of speakers producing stereotype-incongruent utterances. Our findings reveal two potential mechanisms: a speaker-general mechanism that adjusts overall expectations about speaker-content relationships, and a speaker-specific mechanism that updates individual speaker models. In two EEG experiments, participants heard speakers make stereotype-congruent or incongruent utterances, with incongruency base rate manipulated between blocks. In Experiment 1, speaker incongruency modulated both high-beta (21-30 Hz) and theta (4-6 Hz) oscillations: incongruent utterances decreased oscillatory power in low base rate condition but increased it in high base rate condition. The theta effect varied with listeners' openness trait: less open participants showed theta increases to speaker-incongruencies, suggesting maintenance of speaker-specific information, while more open participants showed theta decreases, indicating flexible model updating. In Experiment 2, we dissociated base rate from the target speaker by manipulating the overall base rate using an alternative non-target speaker. Only the high-beta effect persisted, showing power decrease for speaker-incongruencies in low base rate condition but no effect in high base rate condition. The high-beta oscillations might reflect the speaker-general adjustment, while theta oscillations may index the speaker-specific model updating. These findings provide evidence for how language processing is shaped by social cognition in real time.
Code (0)
등록된 구현이 없습니다.
Tasks
EEGMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
We Hebben Een Serieus Translatie: Modeling Intercomprehension as Probabilistic Inference
Intercomprehension refers to partial intelligibility of an unfamiliar language (L2) by a speaker of a related language (L1). How is this zero-shot cross-language comprehension possible? In this work, we extend past work …
Dynamik: Syntactically-Driven Dynamic Font Sizing for Emphasis of Key Information
In today's globalized world, there are increasing opportunities for individuals to communicate using a common non-native language (lingua franca). Non-native speakers often have opportunities to listen to foreign languag…
SentenceLanguage Models are Bounded Pragmatic Speakers: Understanding RLHF from a Bayesian Cognitive Modeling Perspective
How do language models "think"? This paper formulates a probabilistic cognitive model called the bounded pragmatic speaker, which can characterize the operation of different variations of language models. Specifically, w…
reinforcement-learningReinforcement LearningFamily Matters: Language Transfer and Merging for Adapting Small LLMs to Faroese
We investigate strategies for adapting small, efficient language models to Faroese, a low-resource North Germanic language. Starting from English-pretrained models, we apply continued pre-training on related Scandinavian…
Linguistic AcceptabilityReading ComprehensionData-Driven Source Separation Based on Simplex Analysis
Blind source separation (BSS) is addressed, using a novel data-driven approach, based on a well-established probabilistic model. The proposed method is specifically designed for separation of multichannel audio mixtures.…
blind source separation