Music Genre Classification Based on Convolutional Neural Networks and Transformer

With the proliferation of the Internet, an increasing number of people have grown accustomed to enjoying music on music streaming software. For music players, classifying the genres of newly released songs, which are emerging in an explosive manner every day, has become a challenging task. This paper aims to explore how to efficiently and accurately classify new songs, focusing on the application of currently popular artificial intelligence algorithms. By comparing data from multiple music streaming platforms with high daily activity, this paper analyzes the performance of different algorithms in music genre classification. The results demonstrate that the two algorithms based on Convolutional Neural Networks (CNN) and Transformer both perform excellently in terms of accuracy and efficiency, and can effectively achieve precise classification of music genres. This research not only provides technical support for music streaming services but also lays a foundation for future research in related fields.