The invention discloses a question pair matching method and device based on a deep feature fusion neural network, belongs to the field of natural language processing, and aims to solve the technical problem of how to accurately judge the matching degree of a user question and a standard question and sort out a complete question pair matching model. The technical scheme is that the method comprisesthe following steps: S1, constructing a question pair knowledge base; S2, constructing a question pair matching model training data set; S3, constructing a question pair matching model, comprising the following steps: S301, constructing a character mapping conversion table; S302, constructing an input layer; S303, constructing a character vector mapping layer; S304, constructing a neural networkcoding layer based on depth feature fusion; S305, constructing a text similarity matching layer; and S4, training the question pair matching model and selecting a standard problem. The device comprises a question pair knowledge base construction unit, a question pair matching model training data set generation unit, a question pair matching model construction unit and a question pair matching model training unit.