Zipf, neural networks and SVM for musical genre classification

We present in this paper audio classification schemes that we have experimented in order to perform musical genres classification. This type of classification is a part of a more general domain which is automatic semantic audio classification, the applications of which are more and more numerous in such fields as musical or multimedia databases indexing. Experimental results have shown that the feature set we have developed, based on Zipf laws, associated with a combination of classifiers organized hierarchically according to classes taxonomy allow an efficient classification.