@inproceedings{liu2020you,
author = {Liu, Qian and Chen, Yihong and Chen, Bei and Lou, Jian-Guang and Chen, Zixuan and Zhou, Bin and Zhang, Dongmei},
title = {You Impress Me: Dialogue Generation via Mutual Persona Perception},
booktitle = {ACL 2020},
year = {2020},
month = {July},
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 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. Our code is available on GitHub.},
url = {http://approjects.co.za/?big=en-us/research/publication/you-impress-me-dialogue-generation-via-mutual-persona-perception/},
}