EmpCI: Empathetic response generation with common sense and empathetic intent

Abstract

Empathy plays an important role in human conversations as an ability that enables individuals to understand the emotions and situations of others. Integrating empathy into dialogue systems is a crucial step in making them humanized. Relevant psychological studies have shown that a complete, high-quality empathetic dialogue should consist of the following two stages: (1) Empathetic Perception: the listener needs to perceive the emotional state of the speaker from both cognitive and affective aspects; (2) Empathetic Expression: the appropriate expression is chosen to respond to the perceived information. However, many existing studies on empathetic response generation only focus on one of these stages, resulting in incomplete and insufficiently empathetic responses. To this end, we propose the EmpCI, a two-stage empathetic response generation model that utilizes commonsense knowledge and mixed empathetic intent, respectively. Specifically, we use commonsense knowledge in the first stage to enhance the model’s perception of the user’s emotion and introduce mixed empathetic intent in the second stage to generate responses with appropriate expressions for the perceived information. Finally, we evaluated the EmpCI on the EmpatheticDialogues dataset, and extensive experiment results show that the proposed model outperforms the baselines in both perceiving users’ emotions and generating empathetic responses.