Music Style Classification with a Novel Bayesian Model
Music style classification by mean of computers is very useful to music indexing, content-based music retrieval and other multimedia applications. This paper presents a new method for music style classification with a novel Bayesian-inference-based decision tree (BDT) model. A database of total 320 music staffs collected from CDs and the Internet is used for the experiment. For classification three features including the number of sharp octave (NSO), the number of simple meters (NSM), and the music playing speed (MPS) are extracted. Following that, acomparative evaluation between BDT and traditional decision tree (DT) model is carried out on the database. The results show that the classification accuracy rate of BDT far superior to existing DT model.
KeywordsBayesian Model Decision Tree Model Classification Framework Classification Accuracy Rate Music Style
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- 1.Qin, D., Ma, G.Z.: Music style identification system based on mining technology. Computer Engineering and Design 26, 3094–3096 (2005)Google Scholar
- 2.Ma, G.Z., Qin, D.: Music style classification using mutual information (in Chinese). Computer Applications 25, 1116–1118 (2005)Google Scholar
- 3.Kuo, F.F., Shan, M.K.: A personalized music filtering system based on melody style classification. In: Blum (ed.) Proc. IEEE Int. Conf. Data Mining, pp. 649–652 (2002)Google Scholar
- 5.Zhang, Y.B., Zhou, J.: A study on content-based music classification. In: Jordan (ed.) Proc. 7th Int. Sym. Signal Processing and Its Applications, vol. 2, pp. 113–116. Paris, France (2003)Google Scholar
- 7.Xu, C.S., Maddage, N.C., Shao, X.: Automatic music classification and summarization. IEEE Trans. Speech and Audio Processing 3, 441–450 (2005)Google Scholar
- 9.Denson, D.G.T.: Simulation based Bayesian nonparametric regression methods. Ph.D Dissertation. Imperial College, London University (2001)Google Scholar