WU Yunbing1,2, YE Chenglong1,2, YIN Aiying2,3, CHEN Kaizhi1,2, YANG Zhou1,2
1. College of Computer and Data Science, Fuzhou University, Fuzhou 350108 2. Digital Fujian Institute of Financial Big Data, Fuzhou University, Fuzhou 350108 3. Department of Computer Engineering, Zhicheng College, Fu-zhou University, Fuzhou 350002 on EmpatheticDialogues dataset indicate that PERG achieves superior performance in multiple metrics.
Abstract Empathetic response generation aims to understand the experiences and feelings of users in conversations and provide appropriate responses. Psychological theories suggest that roles serve as an external manifestation of personality and are closely related to empathy. However, existing research primarily focuses on the cognitive and emotional factors of empathy while neglecting role factors that are beneficial to empathy, resulting in a lack of personalized empathetic responses. To address this issue, a persona-enhanced empathetic response generation model(PERG) is proposed. A persona-enhanced encoding module is introduced to capture deep semantic relationships among context, situation and role information through an encoder. By filtering role information based on context and situation, the understanding of the speaker′s and responder′s roles by the model is significantly improved, and thereby enhancing its empathetic capabilities. In the persona control decoding module, a multi-decoder control fusion mechanism is designed. The role information is effectively combined to regulate the impact of context and situation on empathy responses , generating highly personalized empathetic responses. Experiments
Fund:National Natural Science Foundation of China(No.62476060), Natural Science Foundation of Fujian Province(No.2022J01116,2022J01119)
Corresponding Authors:
WU Yunbing, Master, associate professor. His research interests include knowledge representation and sentiment analysis.
About author:: YE Chenglong, Master student. His research interests include empathetic dialogue generation. YIN Aiying, Master, associate professor. Her research interests include text retrieval and data mining. .CHEN Kaizhi, Ph.D., associate profe-ssor. His research interests include computer vision and natural language processing. YANG Zhou, Ph.D. candidate. His research interests include empathetic dialogue generation and sentiment analysis.
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