Multi-Party Empathetic Dialogue Generation: A New Task for Dialog Systems
Ling.Yu Zhu, Zhengkun Zhang, Jun Wang, Hongbin Wang, Haiying Wu, Zhenglu Yang · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · 2022
Empathetic dialogue assembles emotion understanding, feeling projection, and appropriate response generation.Existing work for empathetic dialogue generation concentrates on the two-party conversation scenario.Multiparty 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.