Factors in automatic musical genre classification of audio signals

Automatic musical genre classification is an important tool for organizing the large collections of music that are becoming available to the average user. In addition, it provides a structured way of evaluating musical content features that does not require extensive user studies. The paper provides a detailed comparative analysis of various factors affecting automatic classification performance, such as choice of features and classifiers. Using recent machine learning techniques, such as support vector machines, we improve on previously published results using identical data collections and features.