Features for audio and music classification

Four audio feature sets are evaluated in their ability to classify five general audio classes and seven pop-ular music genres. The feature sets include low-level signal properties, mel-frequency spectral coefficients, and two new sets based on perceptual models of hear-ing. The temporal behavior of the features is ana-lyzed and parameterized and these parameters are in-cluded as additional features. Using a standard Gaus-sian framework for classification, results show that the temporal behavior of features is important for both music and audio classification. In addition, classifica-tion is better, on average, if based on features from models of auditory perception rather than on standard features.