The invention discloses an improved DCNN music genre classification method. The method comprises the steps of inputting a training set and a verification set, extracting MFCC features of the audio information, generating a frequency spectrum, carrying out frequency spectrum cutting, inputting a network model, training a model, verifying the model, judging whether a specified batch is reached or not, and outputting a model. According to the method, self-adaption of channel dimensions is achieved through a function, so that the coverage range of interaction of local area cross channels is ensured, an ECA module is more effectively integrated into an existing DCNN architecture, obvious performance gain is brought to a network model, and then the working efficiency of music genre classification is improved. Through the Mel-frequency cepstrum coefficient, the perception characteristics of a human auditory system are simulated, and the classification precision is further improved.