Abstract
Conversational Emotion Recognition (CER) is a task to predict the emotion of an utterance in the context of a conversation. Although modeling the conversational context and interactions between speakers has been studied broadly, it is important to consider the speaker’s psychological state, which controls the action and intention of the speaker. The state-of-the-art method introduces CommonSense Knowledge (CSK) to model psychological states in a sequential way (forwards and backwards). However, it ignores the structural psychological interactions between utterances. In this paper, we propose a pSychological-Knowledge-Aware Interaction Graph (SKAIG). In the locally connected graph, the targeted utterance will be enhanced with the information of action inferred from the past context and intention implied by the future context. The utterance is self-connected to consider the present effect from itself. Furthermore, we utilize CSK to enrich edges with knowledge representations and process the SKAIG with a graph transformer. Our method achieves state-of-the-art and competitive performance on four popular CER datasets.- Anthology ID:
- 2021.findings-emnlp.104
- Volume:
- Findings of the Association for Computational Linguistics: EMNLP 2021
- Month:
- November
- Year:
- 2021
- Address:
- Punta Cana, Dominican Republic
- Editors:
- Marie-Francine Moens, Xuanjing Huang, Lucia Specia, Scott Wen-tau Yih
- Venue:
- Findings
- SIG:
- SIGDAT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1204–1214
- Language:
- URL:
- https://aclanthology.org/2021.findings-emnlp.104
- DOI:
- 10.18653/v1/2021.findings-emnlp.104
- Cite (ACL):
- Jiangnan Li, Zheng Lin, Peng Fu, and Weiping Wang. 2021. Past, Present, and Future: Conversational Emotion Recognition through Structural Modeling of Psychological Knowledge. In Findings of the Association for Computational Linguistics: EMNLP 2021, pages 1204–1214, Punta Cana, Dominican Republic. Association for Computational Linguistics.
- Cite (Informal):
- Past, Present, and Future: Conversational Emotion Recognition through Structural Modeling of Psychological Knowledge (Li et al., Findings 2021)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-5/2021.findings-emnlp.104.pdf
- Code
- leqsnan/skaig-erc
- Data
- ATOMIC, DailyDialog, EmoryNLP, IEMOCAP, MELD