TRACE: Temporal Relationship-Aware Conversational Entrainment Detection in Dyadic Speech

2026-06-29

AI Summary

This study investigates emotional entrainment in dyadic spoken conversations, focusing on how social relationships and contextual dynamics shape affective coordination between interlocutors. To this end, the authors introduce DyadEE, a novel dataset comprising both authentic interactions and synthetically perturbed samples, and propose the TRACE framework. TRACE leverages Whisper acoustic embeddings fine-tuned for emotion recognition and models dialogues as window-level sequential interaction trajectories, incorporating relationship-aware mechanisms and temporal context modeling to capture dynamic entrainment patterns. Experimental results demonstrate that the proposed approach achieves a detection accuracy of 97.01% on DyadEE, underscoring the critical role of relational and contextual information in effectively modeling emotional entrainment in dyadic speech.

Abstract

With the proliferation of speech AI agents, understanding emotional entrainment in conversational interaction has become increasingly important. Emotional entrainment is shaped by social relationships and conversational context, influencing affective coordination over time. We introduce DyadEE, a dataset for emotional entrainment detection in dyadic speech interactions, containing both emotionally entrained conversations and synthetic interactions where entrainment is disrupted through partner swapping and emotion resynthesis. We further propose TRACE, a window-level framework that models dyadic interaction as ordered sequences of acoustic embeddings derived from emotion fine-tuned Whisper representations, treating each sample as an interaction trace rather than pooled utterances. Experimental results on DyadEE show that incorporating conversational context and relationship information improves emotional entrainment detection, with TRACE achieving the best accuracy of 97.01%.

Problem

• emotional entrainment
• dyadic speech
• conversational context
• social relationships
• affective coordination

Innovation

• emotional entrainment
• dyadic speech
• TRACE framework
• interaction trace
• Whisper fine-tuning