This paper presents a genre classification algorithm for music data. The proposed methodology relies on note pitch and duration features, derived from the repeating terns and duration histograms of a musical piece, respectively. Note-information histograms have a great capability in capturing a fair amount of information regarding harmonic as well as rhythmic features of different musical genres and pieces, while repeating patterns refer to segments of the piece that are semantically important. Detailed experimental results on intra-classical genres illustrate the significant performance gains due to the proposed features.
展开▼
