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Title: Usul and Makam driven automatic melodic segmentation for Turkish music
Authors: Bozkurt, Barış
Karaosmanoglu, M. Kemal
Karaçalı, Bilge
Ünal, Erdem
Keywords: Makam
Melodic analysis
Melodic grouping
Melodic segmentation
Publisher: Taylor and Francis Ltd.
Source: Bozkurt, B., Karaosmanoğlu, M.K., Karaçalı, B., and Ünal, E. (2014). Usul and Makam driven automatic melodic segmentation for Turkish music. Journal of New Music Research, 43(4), 375-389. doi:10.1080/09298215.2014.924535
Abstract: Automatic melodic segmentation is a topic studied extensively, aiming at developing systems that perform grouping of musical events. Here, we consider the problem of automatic segmentation via supervised learning from a dataset containing segmentation labels of an expert. We present a statistical classification-based segmentation system developed specifically for Turkish makam music. The proposed system uses two novel features, a makam-based and an usul-based feature, together with features commonly used in literature. The makam-based feature is defined as the probability of a note to appear at the phrase boundary, computed from the distributions of boundaries with respect to the piece’s makam pitches. Likewise, the usul-based feature is computed from the distributions of boundaries with respect to beats in the rhythmic cycle, usul of the piece. Several experimental setups using different feature groups are designed to test the contribution of the proposed features on three datasets. The results show that the new features carry complementary information to existing features in the literature within the Turkish makam music segmentation context and that the inclusion of new features resulted in statistically significant performance improvement.
ISSN: 0929-8215
Appears in Collections:Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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