Don't Lose Yourself! Empathetic Response Generation via Explicit Self-Other Awareness

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Abstract

As a critical step to achieve human-like chatbots, empathetic response generation has attained increasing interests. Previous attempts are incomplete and not sufficient enough to elicit empathy because they only stay on the initial stage of empathy to automatically sense and simulate the feelings and thoughts of others via other-awareness. However, they ignore to include self-awareness to consider the own views of the self in their responses, which is a crucial process to achieve the empathy. To this end, we propose to generate Empathetic response with explicit Self-Other Awareness (EmpSOA). Specifically, three stages, self-other differentiation, self-other modulation and self-other generation, are devised to clearly maintain, regulate and inject the self-other aware information into the process of empathetic response generation. Both automatic and human evaluations on the benchmark dataset demonstrate the superiority of EmpSOA to generate more empathetic responses. Our source code is available at https://github.com/circle-hit/EmpSOA.

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APA

Zhao, W., Zhao, Y., Lu, X., & Qin, B. (2023). Don’t Lose Yourself! Empathetic Response Generation via Explicit Self-Other Awareness. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (pp. 13331–13344). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2023.findings-acl.843

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