AI RESEARCH
Dual-branch Graph Domain Adaptation for Cross-scenario Multi-modal Emotion Recognition
arXiv CS.AI
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ArXi:2603.26840v1 Announce Type: cross Multimodal Emotion Recognition in Conversations (MERC) aims to predict speakers' emotional states in multi-turn dialogues through text, audio, and visual cues. In real-world settings, conversation scenarios differ significantly in speakers, topics, styles, and noise levels. Existing MERC methods generally neglect these cross-scenario variations, limiting their ability to transfer models trained on a source domain to unseen target domains.