Abstract
In multidimensional dialogues, emotions serve not only as crucial mediators of emotional exchanges but also carry rich information. Therefore, accurately identifying the emotions of interlocutors and understanding the triggering factors of emotional changes are paramount. This study focuses on the tasks of multilingual dialogue emotion recognition and emotion reversal reasoning based on provocateurs, aiming to enhance the accuracy and depth of emotional understanding in dialogues. To achieve this goal, we propose a novel model, MBERT-TextRCNN-PL, designed to effectively capture emotional information of interlocutors. Additionally, we introduce XGBoost-EC (Emotion Capturer) to identify emotion provocateurs, thereby delving deeper into the causal relationships behind emotional changes. By comparing with state-of-the-art models, our approach demonstrates significant improvements in recognizing dialogue emotions and provocateurs, offering new insights and methodologies for multilingual dialogue emotion understanding and emotion reversal research.- Anthology ID:
- 2024.semeval-1.48
- Volume:
- Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)
- Month:
- June
- Year:
- 2024
- Address:
- Mexico City, Mexico
- Editors:
- Atul Kr. Ojha, A. Seza Doğruöz, Harish Tayyar Madabushi, Giovanni Da San Martino, Sara Rosenthal, Aiala Rosá
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 311–315
- Language:
- URL:
- https://preview.aclanthology.org/add_missing_videos/2024.semeval-1.48/
- DOI:
- 10.18653/v1/2024.semeval-1.48
- Cite (ACL):
- Wei Tian, Peiyu Ji, Lei Zhang, and Yue Jian. 2024. TW-NLP at SemEval-2024 Task10: Emotion Recognition and Emotion Reversal Inference in Multi-Party Dialogues.. In Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024), pages 311–315, Mexico City, Mexico. Association for Computational Linguistics.
- Cite (Informal):
- TW-NLP at SemEval-2024 Task10: Emotion Recognition and Emotion Reversal Inference in Multi-Party Dialogues. (Tian et al., SemEval 2024)
- PDF:
- https://preview.aclanthology.org/add_missing_videos/2024.semeval-1.48.pdf