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Empathy is an important characteristic to be considered when building a moreintelligent and humanized dialogue agent. However, existing methods did notfully comprehend empathy as a complex process involving three aspects:cognition, affection and behavior. In this paper, we propose CAB, a novelframework that takes a comprehensive perspective of cognition, affection andbehavior to generate empathetic responses. For cognition, we build pathsbetween critical keywords in the dialogue by leveraging external knowledge.This is because keywords in a dialogue are the core of sentences. Building thelogic relationship between keywords, which is overlooked by the majority ofexisting works, can improve the understanding of keywords and contextual logic,thus enhance the cognitive ability. For affection, we capture the emotionaldependencies with dual latent variables that contain both interlocutors'emotions. The reason is that considering both interlocutors' emotionssimultaneously helps to learn the emotional dependencies. For behavior, we useappropriate dialogue acts to guide the dialogue generation to enhance theempathy expression. Extensive experiments demonstrate that ourmulti-perspective model outperforms the state-of-the-art models in bothautomatic and manual evaluation.

CAB: Empathetic Dialogue Generation with Cognition, Affection and Behavior