Dynamic Semantic–Prosodic Integration in Emotional Speech Perception: From Channel Dominance to Precision-Weighted Predictive Coding
Year: 2026
Type: preprint
Abstract: Emotional speech is an important carrier of affective information in spoken communication. Its perception depends on the joint processing of emotional semantics and prosody, yet the relative contribution of these two information sources varies across individuals and contexts. However, a unified account is still lacking of why their processing weights change and how the brain dynamically adjusts them according to the reliability of incoming information. This review synthesizes evidence on emotional semantics and prosody, from relatively independent processing to interactive integration, and argues that their relationship is best understood in terms of dynamic weight allocation. On this basis, we propose a Precision-Weighted Predictive Coding Model (PW-PC), which integrates Bayesian inference, cue precision, and prediction error within a unified framework. The model assumes that semantic and prosodic information are continuously reweighted according to current evidence and its estimated precision, while incorporating sensory reliability, experience-based expectations, contextual diagnosticity, and reweighting flexibility. This framework shifts the focus of emotional speech research from identifying which channel dominates to explaining when, why, and how the brain dynamically reallocates weight across multiple affective information sources, thereby providing a unified theoretical perspective linking behavioral performance, neural dynamics, and computational mechanisms.
Source: PsyArXiv (OSF Preprints)
Authors: Yi Lin, Yang Zhang
Language: English
Subfield: Experimental and Cognitive Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7215117313