DialogueGCN: A Graph Convolutional Neural Network for Emotion Recognition in Conversation

Deepanway Ghosal, Navonil Majumder, Soujanya Poria, Niyati Chhaya, Alexander Gelbukh


Abstract
Emotion recognition in conversation (ERC) has received much attention, lately, from researchers due to its potential widespread applications in diverse areas, such as health-care, education, and human resources. In this paper, we present Dialogue Graph Convolutional Network (DialogueGCN), a graph neural network based approach to ERC. We leverage self and inter-speaker dependency of the interlocutors to model conversational context for emotion recognition. Through the graph network, DialogueGCN addresses context propagation issues present in the current RNN-based methods. We empirically show that this method alleviates such issues, while outperforming the current state of the art on a number of benchmark emotion classification datasets.
Anthology ID:
D19-1015
Volume:
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
Month:
November
Year:
2019
Address:
Hong Kong, China
Venues:
EMNLP | IJCNLP
SIG:
SIGDAT
Publisher:
Association for Computational Linguistics
Note:
Pages:
154–164
Language:
URL:
https://aclanthology.org/D19-1015
DOI:
10.18653/v1/D19-1015
Bibkey:
Cite (ACL):
Deepanway Ghosal, Navonil Majumder, Soujanya Poria, Niyati Chhaya, and Alexander Gelbukh. 2019. DialogueGCN: A Graph Convolutional Neural Network for Emotion Recognition in Conversation. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pages 154–164, Hong Kong, China. Association for Computational Linguistics.
Cite (Informal):
DialogueGCN: A Graph Convolutional Neural Network for Emotion Recognition in Conversation (Ghosal et al., EMNLP 2019)
Copy Citation:
PDF:
https://aclanthology.org/D19-1015.pdf
Code
 SenticNet/conv-emotion +  additional community code
Data
IEMOCAPMELDSEMAINE