You impress me: Dialogue generation via mutual persona perception

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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 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.

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APA

Liu, Q., Chen, Y., Chen, B., Lou, J. G., Chen, Z., Zhou, B., & Zhang, D. (2020). You impress me: Dialogue generation via mutual persona perception. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (pp. 1417–1427). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2020.acl-main.131

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