Abstract
The current music style classification method is based on high-dimensional feature matrix, which has the problem of large space cost and low classification accuracy. In view of the above problems, this paper studies the music style classification method based on neural network. The MFCC features of music are extracted by processing the music to be classified in two steps: weighting and windowing. The RNN neural network is trained by the sample music set to classify the music styles. Simulation results show that compared with the traditional method, the proposed music style classification method improves the classification accuracy by at least 16.36%, and the space and time cost of the method is small, and the practical application effect is better.
Published Version
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