摘要：With the continuous development of information technology, data transmission bandwidth and speed also increase. Therefore, how to retrieve their favorite music quickly and effectively has become a key research direction at present. Genre is one of the most mentioned music labels. Music detection by genre has become the mainstream method of the music information search. It is also an important part of the music service platform to recommend music. Therefore, music genre recognition has attracted much attention and become the mainstream direction of research. This article presents a music genre recognition method based on the improved Bayesian algorithm. The variational modal decomposition is optimized by particle swarm optimization with the variable step size. Then the naive Bayesian network model is constructed to detect music genres. Experimental results show that the proposed algorithm can efficiently extract music feature information, fully consider the particularity of different situations, and improve the accuracy of music genre recognition.
