Dynamic Fusion Network for Multi-Domain End-to-end Task-Oriented Dialog

Libo Qin, Xiao Xu, Wanxiang Che, Yue Zhang, Ting Liu


Abstract
Recent studies have shown remarkable success in end-to-end task-oriented dialog system. However, most neural models rely on large training data, which are only available for a certain number of task domains, such as navigation and scheduling. This makes it difficult to scalable for a new domain with limited labeled data. However, there has been relatively little research on how to effectively use data from all domains to improve the performance of each domain and also unseen domains. To this end, we investigate methods that can make explicit use of domain knowledge and introduce a shared-private network to learn shared and specific knowledge. In addition, we propose a novel Dynamic Fusion Network (DF-Net) which automatically exploit the relevance between the target domain and each domain. Results show that our models outperforms existing methods on multi-domain dialogue, giving the state-of-the-art in the literature. Besides, with little training data, we show its transferability by outperforming prior best model by 13.9% on average.
Anthology ID:
2020.acl-main.565
Volume:
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
Month:
July
Year:
2020
Address:
Online
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
6344–6354
Language:
URL:
https://aclanthology.org/2020.acl-main.565
DOI:
10.18653/v1/2020.acl-main.565
Bibkey:
Cite (ACL):
Libo Qin, Xiao Xu, Wanxiang Che, Yue Zhang, and Ting Liu. 2020. Dynamic Fusion Network for Multi-Domain End-to-end Task-Oriented Dialog. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 6344–6354, Online. Association for Computational Linguistics.
Cite (Informal):
Dynamic Fusion Network for Multi-Domain End-to-end Task-Oriented Dialog (Qin et al., ACL 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.acl-main.565.pdf
Video:
 http://slideslive.com/38929065
Code
 LooperXX/DF-Net
Data
MultiWOZ