Research on Music Style Classification and Recognition Method Based on Probabilistic Neural Network

In the throes of the digital revolution, the processes of musical creation and dissemination have undergone profound transformations, presenting unprecedented challenges and opportunities for the categorization of music styles. The multifaceted nature of music has rendered traditional classification methods increasingly inadequate, while novel approaches based on probabilistic neural networks have demonstrated significant potential. By delving deeply into the extraction of features from musical files and leveraging the classification prowess of probabilistic neural networks, achieving efficient and accurate identification of musical styles has become a focal point of research. This study not only offers fresh perspectives in the realm of music information retrieval but also holds substantial practical significance for applications such as music recommendation systems, music generation, and mixing. It aims to ensure that in the face of the ever-evolving and complex musical landscape, the core characteristics of music can be accurately captured, thereby enhancing user experience.