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Perception and expression of emotion are key factors to the success ofdialogue systems or conversational agents. However, this problem has not beenstudied in large-scale conversation generation so far. In this paper, wepropose Emotional Chatting Machine (ECM) that can generate appropriateresponses not only in content (relevant and grammatical) but also in emotion(emotionally consistent). To the best of our knowledge, this is the first workthat addresses the emotion factor in large-scale conversation generation. ECMaddresses the factor using three new mechanisms that respectively (1) modelsthe high-level abstraction of emotion expressions by embedding emotioncategories, (2) captures the change of implicit internal emotion states, and(3) uses explicit emotion expressions with an external emotion vocabulary.Experiments show that the proposed model can generate responses appropriate notonly in content but also in emotion.

Emotional Chatting Machine: Emotional Conversation Generation with Internal and External Memory