UWBA at SemEval-2024 Task 3: Dialogue Representation and Multimodal Fusion for Emotion Cause Analysis
Josef Baloun, Jiřı́ Martı́nek, Ladislav Lenc, Pavel Král, Matěj Zeman, Lukáš Vlček · 2024
In this paper, we present an approach for solving SemEval-2024 Task 3: The Competition of Multimodal Emotion Cause Analysis in Conversations.The task includes two subtasks that focus on emotion-cause pair extraction using text, video, and audio modalities.Our approach is composed of encoding all modalities (MFCC and Wav2Vec for audio, 3D-CNN for video, and transformer-based models for text) and combining them in an utterancelevel fusion module.The model is then optimized for link and emotion prediction simultaneously.Our approach achieved 6th place in both subtasks.The full leaderboard can be found at https://codalab.lisn.upsaclay. fr/competitions/16141#results.