A Syntactically Constrained Bidirectional-Asynchronous Approach for Emotional Conversation Generation

Jingyuan Li, Xiao Sun


Abstract
Traditional neural language models tend to generate generic replies with poor logic and no emotion. In this paper, a syntactically constrained bidirectional-asynchronous approach for emotional conversation generation (E-SCBA) is proposed to address this issue. In our model, pre-generated emotion keywords and topic keywords are asynchronously introduced into the process of decoding. It is much different from most existing methods which generate replies from the first word to the last. Through experiments, the results indicate that our approach not only improves the diversity of replies, but gains a boost on both logic and emotion compared with baselines.
Anthology ID:
D18-1071
Volume:
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
Month:
October-November
Year:
2018
Address:
Brussels, Belgium
Editors:
Ellen Riloff, David Chiang, Julia Hockenmaier, Jun’ichi Tsujii
Venue:
EMNLP
SIG:
SIGDAT
Publisher:
Association for Computational Linguistics
Note:
Pages:
678–683
Language:
URL:
https://aclanthology.org/D18-1071
DOI:
10.18653/v1/D18-1071
Bibkey:
Cite (ACL):
Jingyuan Li and Xiao Sun. 2018. A Syntactically Constrained Bidirectional-Asynchronous Approach for Emotional Conversation Generation. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pages 678–683, Brussels, Belgium. Association for Computational Linguistics.
Cite (Informal):
A Syntactically Constrained Bidirectional-Asynchronous Approach for Emotional Conversation Generation (Li & Sun, EMNLP 2018)
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PDF:
https://aclanthology.org/D18-1071.pdf