QFNU_CS at SemEval-2024 Task 3: A Hybrid Pre-trained Model based Approach for Multimodal Emotion-Cause Pair Extraction Task
Zining Wang, Yanchao Zhao, Guanghui Han, Yang Song · 2024
This article presents the solution of Qufu Normal University for the Multimodal Sentiment Cause Analysis competition in Se-mEval2024 Task 3.The competition aims to extract emotion-cause pairs from dialogues containing text, audio, and video modalities.To cope with this task, we employ a hybrid pre-train model based approach.Specifically, we first extract and fusion features from dialogues based on BERT, BiLSTM, openSMILE and C3D.Then, we adopt BiLSTM and Transformer to extract the candidate emotion-cause pairs.Finally, we design a filter to identify the correct emotion-cause pairs.The evaluation results show that, we achieve a weighted average F1 score of 0.1786 and an F1 score of 0.1882 on CodaLab.