The invention discloses a construction method of hybrid neural network model for dialogue generation. The construction method of hybrid neural network model for dialogue generation includes the steps: acquiring a data set in a mode of dialogue statement pairs, and constructing a glossary; generating a word embedded table; initializing the convolution neural network with special structure, generating a vocabulary recommending table corresponding to the input statement, determining whether real output is provided, and if so, training the parameters of the convolution neural network in the step; initializing the recurrent neural network with special structure, using the last step to output, generating a vocabulary identity list with word order, determining whether real output is provided, and if so, training the parameters of the recurrent neural network in the step; after the training result satisfies the set index, saving the glossary and the word embedded table, and saving the parameters of the convolution neural network and the recurrent neural network, thus completing construction of the whole model. The construction method of hybrid neural network model for dialogue generation solves the problems that a current neural network dialogue model is slow in the training speed, low in the accuracy and general in statement generation because the glossary is too long.