You Impress Me: Dialogue Generation via Mutual Persona Perception

被引:0
|
作者
Lin, Qian [1 ]
Chen, Yihong [2 ]
Chen, Bei [4 ]
Lou, Jian-Guang [4 ]
Chen, Zixuan [3 ]
Zhou, Bin [1 ]
Zhang, Dongmei [4 ]
机构
[1] Beihang Univ, Sch Comp Sci & Engn, Beijing, Peoples R China
[2] UCL, UCL Ctr Artificial Intelligence, London, England
[3] Fudan Univ, Sch Comp Sci, Shanghai, Peoples R China
[4] Microsoft Res, Beijing, Peoples R China
基金
国家重点研发计划; 中国国家自然科学基金;
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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 P-2 BOT, a transmitter-receiver based framework with the aim of explicitly modeling understanding. Specifically, P-2 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.
引用
收藏
页码:1417 / 1427
页数:11
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