You Impress Me: Dialogue Generation via Mutual Persona Perception

Qian Liu, Yihong Chen, Bei Chen, Jian-Guang Lou, Zixuan Chen, Bin Zhou, Dongmei Zhang


Abstract
Despite the continuing efforts to improve the engagingness and consistency of chit-chat dialogue systems, the majority of current work simply focus on mimicking human-like responses, leaving understudied the aspects of modeling understanding between interlocutors. The research in cognitive science, instead, suggests that understanding is an essential signal for a high-quality chit-chat conversation. Motivated by this, we propose Pˆ2 Bot, a transmitter-receiver based framework with the aim of explicitly modeling understanding. Specifically, Pˆ2 Bot incorporates mutual persona perception to enhance the quality of personalized dialogue generation. Experiments on a large public dataset, Persona-Chat, demonstrate the effectiveness of our approach, with a considerable boost over the state-of-the-art baselines across both automatic metrics and human evaluations.
Anthology ID:
2020.acl-main.131
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:
1417–1427
Language:
URL:
https://aclanthology.org/2020.acl-main.131
DOI:
10.18653/v1/2020.acl-main.131
Bibkey:
Cite (ACL):
Qian Liu, Yihong Chen, Bei Chen, Jian-Guang Lou, Zixuan Chen, Bin Zhou, and Dongmei Zhang. 2020. You Impress Me: Dialogue Generation via Mutual Persona Perception. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 1417–1427, Online. Association for Computational Linguistics.
Cite (Informal):
You Impress Me: Dialogue Generation via Mutual Persona Perception (Liu et al., ACL 2020)
Copy Citation:
PDF:
https://preview.aclanthology.org/update-css-js/2020.acl-main.131.pdf
Video:
 http://slideslive.com/38928693
Code
 SivilTaram/Persona-Dialogue-Generation
Data
PERSONA-CHAT