Intention Reasoning Network for Multi-Domain End-to-end Task-Oriented Dialogue

Zhiyuan Ma, Jianjun Li, Zezheng Zhang, Guohui Li, Yongjing Cheng


Abstract
Recent years has witnessed the remarkable success in end-to-end task-oriented dialog system, especially when incorporating external knowledge information. However, the quality of most existing models’ generated response is still limited, mainly due to their lack of fine-grained reasoning on deterministic knowledge (w.r.t. conceptual tokens), which makes them difficult to capture the concept shifts and identify user’s real intention in cross-task scenarios. To address these issues, we propose a novel intention mechanism to better model deterministic entity knowledge. Based on such a mechanism, we further propose an intention reasoning network (IR-Net), which consists of joint and multi-hop reasoning, to obtain intention-aware representations of conceptual tokens that can be used to capture the concept shifts involved in task-oriented conversations, so as to effectively identify user’s intention and generate more accurate responses. Experimental results verify the effectiveness of IR-Net, showing that it achieves the state-of-the-art performance on two representative multi-domain dialog datasets.
Anthology ID:
2021.emnlp-main.174
Volume:
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Month:
November
Year:
2021
Address:
Online and Punta Cana, Dominican Republic
Editors:
Marie-Francine Moens, Xuanjing Huang, Lucia Specia, Scott Wen-tau Yih
Venue:
EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
2273–2285
Language:
URL:
https://aclanthology.org/2021.emnlp-main.174
DOI:
10.18653/v1/2021.emnlp-main.174
Bibkey:
Cite (ACL):
Zhiyuan Ma, Jianjun Li, Zezheng Zhang, Guohui Li, and Yongjing Cheng. 2021. Intention Reasoning Network for Multi-Domain End-to-end Task-Oriented Dialogue. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 2273–2285, Online and Punta Cana, Dominican Republic. Association for Computational Linguistics.
Cite (Informal):
Intention Reasoning Network for Multi-Domain End-to-end Task-Oriented Dialogue (Ma et al., EMNLP 2021)
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PDF:
https://aclanthology.org/2021.emnlp-main.174.pdf
Video:
 https://aclanthology.org/2021.emnlp-main.174.mp4