Abstract
Due to the diverse properties of music, music can be categorized into many types, generating huge amounts of music style classification systems to be proposed. According to musicology, melody, rhythm, harmony and other features can be employed in discriminating styles of the music. In other words, every music genre has its own specific features. In this thesis, we present a method of feature extraction based on the characteristic of the rock music style and musicology. Two features, i.e., chord and rhythm (bass and percussion), are extracted from the music objects for music classification. After feature extraction, the feature vectors of the training music objects are used as the input for the SVM classifier. The generated classification model is then adopted to discriminate one music style from another. We perform three series of experiments to show the accuracy of classification results.