Emotion Guidance Dialogue Response Generation Model

Although existing emotion dialogue generation models can generate reply statements with emotions, they do not consider the problem of poor emotional experience caused by changes in the emotions of both parties in the dialogue. To solve the above problems and realize emotion dialogue response generation, this paper proposes an emotion response generation method EGRGM based on deep neural network. It identifies user emotion and decides to reply emotion during the dialogue, and finally controls the generation of emotion response to realize the guidance of user emotion. The experimental results show that the EGRGM model achieves good results in terms of emotion guidance ability, emotion expression ability and content quality compared with the baseline model, which verifies the response generation ability of this model in emotion dialogues.