Abstract

Automatic music genre classification is a fundamental component of music information retrieval systems and has been gaining importance and enjoying a growing amount of attention with the emergence of digital music on the Internet. Although considerable research has been conducted in automatic music genre classification, little has been done on hierarchical classification with taxonomies. The underlying hierarchical taxonomy identifies the relationships of dependence between different genres and provides valuable sources of information for genre classification. This paper investigates the use of taxonomy for music genre classification. Our empirical experiments on two datasets show that using taxonomy improves the classification performance. We also propose an approach for automatically generating genre taxonomies based on the confusion matrix via linear discriminant projection. Our work also provides some insights for future research. 1.

Citations