Generating Responses with a Specific Emotion in Dialog

Zhenqiao Song, Xiaoqing Zheng, Lu Liu, Mu Xu, Xuanjing Huang


Abstract
It is desirable for dialog systems to have capability to express specific emotions during a conversation, which has a direct, quantifiable impact on improvement of their usability and user satisfaction. After a careful investigation of real-life conversation data, we found that there are at least two ways to express emotions with language. One is to describe emotional states by explicitly using strong emotional words; another is to increase the intensity of the emotional experiences by implicitly combining neutral words in distinct ways. We propose an emotional dialogue system (EmoDS) that can generate the meaningful responses with a coherent structure for a post, and meanwhile express the desired emotion explicitly or implicitly within a unified framework. Experimental results showed EmoDS performed better than the baselines in BLEU, diversity and the quality of emotional expression.
Anthology ID:
P19-1359
Volume:
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
Month:
July
Year:
2019
Address:
Florence, Italy
Editors:
Anna Korhonen, David Traum, Lluís Màrquez
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
3685–3695
Language:
URL:
https://aclanthology.org/P19-1359
DOI:
10.18653/v1/P19-1359
Bibkey:
Cite (ACL):
Zhenqiao Song, Xiaoqing Zheng, Lu Liu, Mu Xu, and Xuanjing Huang. 2019. Generating Responses with a Specific Emotion in Dialog. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 3685–3695, Florence, Italy. Association for Computational Linguistics.
Cite (Informal):
Generating Responses with a Specific Emotion in Dialog (Song et al., ACL 2019)
Copy Citation:
PDF:
https://aclanthology.org/P19-1359.pdf