Multi-Domain Dialogue Acts and Response Co-Generation

Kai Wang, Junfeng Tian, Rui Wang, Xiaojun Quan, Jianxing Yu


Abstract
Generating fluent and informative responses is of critical importance for task-oriented dialogue systems. Existing pipeline approaches generally predict multiple dialogue acts first and use them to assist response generation. There are at least two shortcomings with such approaches. First, the inherent structures of multi-domain dialogue acts are neglected. Second, the semantic associations between acts and responses are not taken into account for response generation. To address these issues, we propose a neural co-generation model that generates dialogue acts and responses concurrently. Unlike those pipeline approaches, our act generation module preserves the semantic structures of multi-domain dialogue acts and our response generation module dynamically attends to different acts as needed. We train the two modules jointly using an uncertainty loss to adjust their task weights adaptively. Extensive experiments are conducted on the large-scale MultiWOZ dataset and the results show that our model achieves very favorable improvement over several state-of-the-art models in both automatic and human evaluations.
Anthology ID:
2020.acl-main.638
Volume:
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
Month:
July
Year:
2020
Address:
Online
Editors:
Dan Jurafsky, Joyce Chai, Natalie Schluter, Joel Tetreault
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
7125–7134
Language:
URL:
https://aclanthology.org/2020.acl-main.638
DOI:
10.18653/v1/2020.acl-main.638
Bibkey:
Cite (ACL):
Kai Wang, Junfeng Tian, Rui Wang, Xiaojun Quan, and Jianxing Yu. 2020. Multi-Domain Dialogue Acts and Response Co-Generation. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 7125–7134, Online. Association for Computational Linguistics.
Cite (Informal):
Multi-Domain Dialogue Acts and Response Co-Generation (Wang et al., ACL 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.acl-main.638.pdf
Video:
 http://slideslive.com/38928730
Code
 InitialBug/MarCo-Dialog