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Classification of classic Turkish music makams by using deep belief networks

Automatic classification of makams from sound data is a challenging yet rarely studied topic. In this work, it is aimed to develop an MIR system which determines a song's makam. To overcome this problem, mel frequency cepstral coefficients were utilized as features. Five classifiers were considered. The best result was obtained by deep belief network as 93.10 which is comparable to the recent works.