Jinming Zhao, Tenggan Zhang, Jingwen Hu, Yuchen Liu, Qin Jin, Xinchao Wang, Haizhou Li. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2022.

Emotion Recognition in Conversation (ERC) has attracted increasing attention in the affective computing research field. Previous works have mainly focused on modeling the semantic interactions in the dialogue and implicitly inferring the evolution of the speakers’ emotional states. Few works have considered the emotional interactions, which directly reflect the emotional evolution of speakers in the dialogue. According to psychological and behavioral studies, the emotional inertia and emotional stimulus are important factors that affect the speaker’s emotional state in conversations. In this work, we propose a novel Dialogue Emotion Interaction Network, DialogueEIN, to explicitly model the intra-speaker, inter-speaker, global and local emotional interactions to respectively simulate the emotional inertia, emotional stimulus, global and local emotional evolution in dialogues. Extensive experiments on four ERC benchmark datasets, IEMOCAP, MELD, EmoryNLP and DailyDialog, show that our proposed DialogueEIN considering emotional interaction factors can achieve superior or competitive performance compared to state-of-the-art methods. Our codes and models are released.

Jingwen Hu, Yuchen Liu, Jinming Zhao, Qin Jin. Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers). 2021.