The Design And Research Of Emotional Response Genration Based On Deep Learning

In recent years,with the research of Internet and computer science and technology,especially the research of deep learning technology,the development of automatic text generation technology has been promoted.The technology of text generation has been widely used in chatting robot,text summary generation,and many other Natural Language Processing related fields such as Machine Translation have made many breakthroughs.Chat dialogue can be regarded as the change and expression of individual emotion.Emotion is an important factor affecting the creation of the content of the dialogue text.This article is devoted to the introduction of emotional intelligence in the text response generation technology.This paper first studies the related technologies and the research status of the dialogue response generation,analyzes the problems and the improvement space of the deep learning technology in the generation of dialogue reply,and probes into the construction of the response generation model based on the emotional intelligence based on the technology of deep learning and emotional analysis,and proposes a multistate migration matrix based on the multiple state migration matrix.Based on the contextual content information,the model is further integrated with the emotion transfer and change information of the dialog text.The experimental results show that emotional intelligence can make text recovery more expressive and more vivid.In order to further explore the value and significance of the algorithm,this paper uses the response generation model as the core technology,and based on the Flask framework,the reply generation model is embedded into the dialogue system as a back end service.The assistant function module is designed,and its design objective and application scenario are discussed.Finally,through the user experience analysis,the dialogic auxiliary function module in this paper can meet the requirements of the people,help and promote people's daily dialogue,and discusses what role the technology plays in the commercial application under the current technology maturity of the dialogue response generation.