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    <abstract>Empathetic dialogue assembles emotion understanding, feeling projection, and appropriate response generation. Existing work for empathetic dialogue generation concentrates on the two-party conversation scenario. Multi-party dialogues, however, are pervasive in reality. Furthermore, emotion and sensibility are typically confused; a refined empathy analysis is needed for comprehending fragile and nuanced human feelings. We address these issues by proposing a novel task called Multi-Party Empathetic Dialogue Generation in this study. Additionally, a Static-Dynamic model for Multi-Party Empathetic Dialogue Generation, SDMPED, is introduced as a baseline by exploring the static sensibility and dynamic emotion for the multi-party empathetic dialogue learning, the aspects that help SDMPED achieve the state-of-the-art performance.</abstract>
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%0 Conference Proceedings
%T Multi-Party Empathetic Dialogue Generation: A New Task for Dialog Systems
%A Zhu, Ling.Yu
%A Zhang, Zhengkun
%A Wang, Jun
%A Wang, Hongbin
%A Wu, Haiying
%A Yang, Zhenglu
%Y Muresan, Smaranda
%Y Nakov, Preslav
%Y Villavicencio, Aline
%S Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2022
%8 May
%I Association for Computational Linguistics
%C Dublin, Ireland
%F zhu-etal-2022-multi
%X Empathetic dialogue assembles emotion understanding, feeling projection, and appropriate response generation. Existing work for empathetic dialogue generation concentrates on the two-party conversation scenario. Multi-party dialogues, however, are pervasive in reality. Furthermore, emotion and sensibility are typically confused; a refined empathy analysis is needed for comprehending fragile and nuanced human feelings. We address these issues by proposing a novel task called Multi-Party Empathetic Dialogue Generation in this study. Additionally, a Static-Dynamic model for Multi-Party Empathetic Dialogue Generation, SDMPED, is introduced as a baseline by exploring the static sensibility and dynamic emotion for the multi-party empathetic dialogue learning, the aspects that help SDMPED achieve the state-of-the-art performance.
%R 10.18653/v1/2022.acl-long.24
%U https://aclanthology.org/2022.acl-long.24
%U https://doi.org/10.18653/v1/2022.acl-long.24
%P 298-307

Markdown (Informal)

[Multi-Party Empathetic Dialogue Generation: A New Task for Dialog Systems](https://aclanthology.org/2022.acl-long.24) (Zhu et al., ACL 2022)

• Multi-Party Empathetic Dialogue Generation: A New Task for Dialog Systems (Zhu et al., ACL 2022)

ACL

• Ling.Yu Zhu, Zhengkun Zhang, Jun Wang, Hongbin Wang, Haiying Wu, and Zhenglu Yang. 2022. Multi-Party Empathetic Dialogue Generation: A New Task for Dialog Systems. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 298–307, Dublin, Ireland. Association for Computational Linguistics.