A machine learning approach to musical style recognition

Much of the work on perception and understanding of music by computers has focused on low-level perceptual features such as pitch and tempo. Our work demonstrates that machine learning can be used to build e ective style classi ers for interactive performance systems. We also present an analysis explaining why these techniques work so well when hand-coded approaches have consistently failed. We also describe a reliable real-time performance style classi er.