情感计算的关系范式转变：情感共振、活力情感与声音交互场
Shifting Relational Paradigms for Affective Computing: Affective Resonance, Vitality Affects, and Vocal Interaction Fields
- Nurobodi
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本文提出以交互场为基本单位的关系性情感计算框架，通过自监督语音表示检测多方对话中的方向性耦合，并设计基于情感共振动态本体论的人工情感共振智能。
AI中文摘要：
情感计算在很大程度上遵循了个体状态范式，即从孤立的说话者中提取离散的情感标签或唤醒度/效价。我们认为，这种框架对于交互而言是不完整的。借鉴情感共振和活力轮廓的理论，我们提出了一种关系框架，其中情感分析的基本单位是在声音动态中构成的交互场。作为概念验证，我们进行了一项初步的实证研究，使用连续的自监督语音表示来检测多方对话中的方向性表达耦合。这种耦合具有特定状态（regime-specific）的特征，集中在亚秒级时间尺度上，并且在仅语音的阴性对照条件下消失，这与情感动态的关系性解释一致。我们引入了基于情感共振动态本体论的人工情感共振智能的设计框架，并得到了跨交互状态的空校准方向性耦合分析的支持。
英文摘要：
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.
