MIPS at SemEval-2024 Task 3: Multimodal Emotion-Cause Pair Extraction in Conversations with Multimodal Language Models
CoRR(2024)
摘要
This paper presents our winning submission to Subtask 2 of SemEval 2024 Task
3 on multimodal emotion cause analysis in conversations. We propose a novel
Multimodal Emotion Recognition and Multimodal Emotion Cause Extraction
(MER-MCE) framework that integrates text, audio, and visual modalities using
specialized emotion encoders. Our approach sets itself apart from
top-performing teams by leveraging modality-specific features for enhanced
emotion understanding and causality inference. Experimental evaluation
demonstrates the advantages of our multimodal approach, with our submission
achieving a competitive weighted F1 score of 0.3435, ranking third with a
margin of only 0.0339 behind the 1st team and 0.0025 behind the 2nd team.
Project: https://github.com/MIPS-COLT/MER-MCE.git
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