TelME: Teacher-leading Multimodal Fusion Network for Emotion Recognition in Conversation

Taeyang Yun, Hyunkuk Lim, Jeonghwan Lee, Min Song


Abstract
Emotion Recognition in Conversation (ERC) plays a crucial role in enabling dialogue sys- tems to effectively respond to user requests. The emotions in a conversation can be identi- fied by the representations from various modal- ities, such as audio, visual, and text. How- ever, due to the weak contribution of non-verbal modalities to recognize emotions, multimodal ERC has always been considered a challenging task. In this paper, we propose Teacher-leading Multimodal fusion network for ERC (TelME). TelME incorporates cross-modal knowledge distillation to transfer information from a lan- guage model acting as the teacher to the non- verbal students, thereby optimizing the efficacy of the weak modalities. We then combine multi- modal features using a shifting fusion approach in which student networks support the teacher. TelME achieves state-of-the-art performance in MELD, a multi-speaker conversation dataset for ERC. Finally, we demonstrate the effec- tiveness of our components through additional experiments.
Anthology ID:
2024.naacl-long.5
Volume:
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
Month:
June
Year:
2024
Address:
Mexico City, Mexico
Editors:
Kevin Duh, Helena Gomez, Steven Bethard
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
82–95
Language:
URL:
https://aclanthology.org/2024.naacl-long.5
DOI:
Bibkey:
Cite (ACL):
Taeyang Yun, Hyunkuk Lim, Jeonghwan Lee, and Min Song. 2024. TelME: Teacher-leading Multimodal Fusion Network for Emotion Recognition in Conversation. In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), pages 82–95, Mexico City, Mexico. Association for Computational Linguistics.
Cite (Informal):
TelME: Teacher-leading Multimodal Fusion Network for Emotion Recognition in Conversation (Yun et al., NAACL 2024)
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PDF:
https://aclanthology.org/2024.naacl-long.5.pdf
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