Papers by Eunseon Seong

1 papers
Emotion-Wheel-Guided Audio-Referred Text Representation for Multimodal Emotion Recognition in Conversation (2026.acl-long)

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Challenge: Existing methods for Emotion Recognition in Conversation ignore their distinct communicative roles and information capacities and apply uniform penalties regardless of affective proximity.
Approach: They propose a modality-aware fusion strategy capturing linguistic features from text as the primary source and audio as a complementary component.
Outcome: The proposed method captures linguistic features from text as the primary source and audio as a complementary component and supervised contrastive loss to encode emotional proximity based on Russell’s circumplex model.

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