Speaker effects in language comprehension: An integrative model of language and speaker processing

TL;DR

This paper reviews how speaker identity influences language comprehension, proposing an integrative probabilistic model that combines perception and expectation mechanisms, with implications for social cognition and AI communication.

Contribution

It introduces a comprehensive model integrating mechanistic perspectives on speaker effects, emphasizing multi-level probabilistic processing and the distinction between speaker-idiosyncrasy and demographic effects.

Findings

Speaker effects are driven by perception and expectation processes.

Language and speaker processing are integrated through probabilistic models.

The framework distinguishes between individual familiarity and social group influences.

Abstract

The identity of a speaker influences language comprehension through modulating perception and expectation. This review explores speaker effects and proposes an integrative model of language and speaker processing that integrates distinct mechanistic perspectives. We argue that speaker effects arise from the interplay between bottom-up perception-based processes, driven by acoustic-episodic memory, and top-down expectation-based processes, driven by a speaker model. We show that language and speaker processing are functionally integrated through multi-level probabilistic processing: prior beliefs about a speaker modulate language processing at the phonetic, lexical, and semantic levels, while the unfolding speech and message continuously update the speaker model, refining broad demographic priors into precise individualized representations. Within this framework, we distinguish between speaker-idiosyncrasy effects arising from familiarity with an individual and speaker-demographics effects arising from social group expectations. We discuss how speaker effects serve as indices for assessing language development and social cognition, and we encourage future research to extend these findings to the emerging domain of artificial intelligence (AI) speakers, as AI agents represent a new class of social interlocutors that are transforming the way we engage in communication.