Shifting Relational Paradigms for Affective Computing: Affective Resonance, Vitality Affects, and Vocal Interaction Fields

Abstract:Affective computing has largely followed an individual-state paradigm, extracting discrete emotion labels or arousal/valence from isolated speakers. We argue this framing is incomplete for interaction. Drawing on affective resonance and vitality-contour accounts, we propose a relational framework in which the primary unit of affective analysis is the interactional field constituted within vocal dynamics. As a proof of concept, we present a preliminary empirical study using continuous self-supervised speech representations to detect directional expressive coupling in multi-party conversation. Coupling is regime-specific, concentrated at sub-second timescales, and collapses under exclusive-speech negative controls, consistent with a relational account of affective dynamics. We introduce design frameworks for Artificial Affective Resonance Intelligence grounded in Affective Resonance Dynamic Ontologies, supported by null-calibrated directional coupling analyses across interaction regimes.

Accepted at Interspeech 2026 for poster presentation. 5 pages, 2 figures, 2 tables

Artificial Intelligence (cs.AI)

arXiv:2609.09864 [cs.AI]

(or arXiv:2609.09864v1 [cs.AI] for this version)

https://doi.org/10.48550/arXiv.2609.09864 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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