TY - GEN
T1 - You impress me
T2 - 58th Annual Meeting of the Association for Computational Linguistics, ACL 2020
AU - Liu, Qian
AU - Chen, Yihong
AU - Chen, Bei
AU - Lou, Jian Guang
AU - Chen, Zixuan
AU - Zhou, Bin
AU - Zhang, Dongmei
N1 - Publisher Copyright:
© 2020 Association for Computational Linguistics
PY - 2020
Y1 - 2020
N2 - 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 P2 BOT, a transmitter-receiver based framework with the aim of explicitly modeling understanding. Specifically, P2 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.
AB - 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 P2 BOT, a transmitter-receiver based framework with the aim of explicitly modeling understanding. Specifically, P2 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.
UR - https://www.scopus.com/pages/publications/85117966953
M3 - 会议稿件
AN - SCOPUS:85117966953
T3 - Proceedings of the Annual Meeting of the Association for Computational Linguistics
SP - 1417
EP - 1427
BT - ACL 2020 - 58th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference
PB - Association for Computational Linguistics (ACL)
Y2 - 5 July 2020 through 10 July 2020
ER -