DialogueCRN: Contextual Reasoning Networks for Emotion Recognition in Conversations

Dou Hu, Lingwei Wei, Xiaoyong Huai


Abstract
Emotion Recognition in Conversations (ERC) has gained increasing attention for developing empathetic machines. Recently, many approaches have been devoted to perceiving conversational context by deep learning models. However, these approaches are insufficient in understanding the context due to lacking the ability to extract and integrate emotional clues. In this work, we propose novel Contextual Reasoning Networks (DialogueCRN) to fully understand the conversational context from a cognitive perspective. Inspired by the Cognitive Theory of Emotion, we design multi-turn reasoning modules to extract and integrate emotional clues. The reasoning module iteratively performs an intuitive retrieving process and a conscious reasoning process, which imitates human unique cognitive thinking. Extensive experiments on three public benchmark datasets demonstrate the effectiveness and superiority of the proposed model.
Anthology ID:
2021.acl-long.547
Volume:
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)
Month:
August
Year:
2021
Address:
Online
Venues:
ACL | IJCNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
7042–7052
Language:
URL:
https://aclanthology.org/2021.acl-long.547
DOI:
10.18653/v1/2021.acl-long.547
Bibkey:
Cite (ACL):
Dou Hu, Lingwei Wei, and Xiaoyong Huai. 2021. DialogueCRN: Contextual Reasoning Networks for Emotion Recognition in Conversations. In 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), pages 7042–7052, Online. Association for Computational Linguistics.
Cite (Informal):
DialogueCRN: Contextual Reasoning Networks for Emotion Recognition in Conversations (Hu et al., ACL-IJCNLP 2021)
Copy Citation:
PDF:
https://preview.aclanthology.org/author-url/2021.acl-long.547.pdf
Video:
 https://preview.aclanthology.org/author-url/2021.acl-long.547.mp4
Code
 zerohd4869/DialogueCRN
Data
IEMOCAPMELDSEMAINE