Dialogue Generation Model Integrating Emotional and Commonsense Knowledge

Abstract

With the development of deep learning technology,as an important branch of human-machine dialogue system,open domain dialogue system has also developed rapidly.However,there are still problems such as poor empathy and low diversity in response sentences generated by existing dialogue models in open domains.To address these problems,a dialogue generation model integrating emotional and commonsense knowledge is proposed in this paper.Commonsense knowledge vector corresponding to each word is firstly obtained based on the emotion dictionary and commonsense knowledge graph,and the vector is input into the encoder for encoding along with the word embedding vector of the word itself.Then a two-stage decodingprocess is used to ge-nerate response sentence:the first decoding stage is to predict the emotional intensity of the word to be generated and obtain the corresponding emotional vector for that word based on it,the second decoding stage combines the encoding result of the first stage with the word embedding vector of the generated word and its corresponding common sense knowledge vector as input to predict the word to be generated.Experimental results show that the response sentences generated by the proposed model are more empathetic and diverse,and it has a certain improvement in PPL,BLEU,ACC and DISTINCT evaluation compared with the baseline models.