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Similarity Measures for Traditional Turkish Art Music
Ali C. Gedik
Pages - 52 - 65     |    Revised - 05-04-2013     |    Published - 30-04-2013
Volume - 7   Issue - 1    |    Publication Date - June 2013  Table of Contents
Similarity Measure, Histogram Comparison, Earth Mover’s Distance, Music Information Retrieval, Traditional Turkish Art Music.
Pitch histograms are frequently used for a wide range of applications in music information retrieval (MIR) which mainly focus on western music. However there are significant differences between pitch spaces of traditional Turkish art music (TTAM) and western music which prevent to apply current methods. In this sense comparison of pitch histograms for TTAM corresponds to the research domain in pattern recognition: finding an appropriate similarity measure in relation with the metric axioms and characteristics of the data. Therefore we have evaluated various similarity measures frequently used in histogram comparison such as L1-norm, L2-norm, histogram intersection, correlation coefficient measures and earth mover’s distance (EMD) for TTAM. Consequently we have discussed one of the problems of the domain, about measures regarding overlap or/and non-overlap between ordinal type histograms and presented an improved version of EMD for TTAM.
CITED BY (1)  
1 Bozkurt, B., Ayangil, R., & Holzapfel, A. (2014). Computational analysis of turkish makam music: Review of state-of-the-art and challenges. Journal of New Music Research, 43(1), 3-23.
1 Google Scholar 
2 CiteSeerX 
3 refSeek 
4 Scribd 
5 SlideShare 
6 PdfSR 
A. C. Gedik and B. Bozkurt. Pitch frequency histogram based music information retrieval for Turkish music, Signal Processing, Vol. 90, No. 4, pp. 1049-1063, 2010.
A. C. Gedik and B. Bozkurt., Evaluation of the Makam Scale Theory of Arel for Music Information Retrieval on Traditional Turkish Art Music, Journal of New Music Research, Vol.38, No. 2, pp. 103-116, 2009.
A. de Cheveigne and H. Kawahara. YIN, a fundamental frequency estimator for speech and music, Journal of the Acoustical Society of America, Vol. 111, No. 4, pp. 1917-1930, 2002.
A. Tversky. Features of similarity. Psychological Review, Vol. 84, No. 4, pp. 327–352,1977.
B. Bozkurt, O.Yarman, M. K. Karaosmanoglu and C. Akkoç. Weighing Diverse Theoretical Models On Turkish Maqam Music Against Pitch Measurements, Journal of New Music Research, Vol. 38, No. 1, pp. 45-70, 2009.
B. Bozkurt. An Automatic Pitch Analysis Method for Turkish Maqam Music, Journal of New Music Research, Vol. 37, No. 1, pp. 1–13, 2008.
C. Akkoç. Non-deterministic scales used in traditional Turkish music, Journal of New Music Research, Vol. 31, No. 4. pp. 285-293. 2002.
D. Temperley. The Cognition of Basic Musical Structures. MIT Press, Cambridge,Massachusetts, 2001
F. Serratosa and A. Sanfeliu. A fast distance between histograms, Lecture Notes on Computer Science, Vol. 3773, pp. 1027 – 1035, 2005.
J. Morovic, J. Shaw, P.L. Sun. A fast, non-iterative and exact histogram matching algorithm,Pattern Recognition Lett., Vol. 23, pp. 127–135, 2002.
J.K., Kamarainen, V. Kyrki, J. Llonen, H. Kälviäinen. Improving similarity measures of histograms using smoothing projections, Pattern Recognition Lett., Vol. 24, pp. 2009–2019,2003.
K. Ito, (ed.). “Metric Space”, Encyclopedic Dictionary of Mathematics, Vol.2, The Mathematical Society of Japan, MIT Press, 2nd edition, 1993.
Ling, H. and Okada, K. An Efficient Earth Mover's Distance Algorithm for Robust Histogram Comparison, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 29, No.5, pp. 840-853, 2007.
M. Das, E.M. Riseman, and B.A. Draper. FOCUS: Searching for multi-colored objects in a diverse image database, In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 1997, pp. 756–761.
M. Rosenlicht. Introduction to analysis, Dover Pub., New York, 1968.
S. H. S. Cha and N. Srihari. On measuring the distance between histograms, Pattern Recognition, Vo. 35, pp. 1355–1370, 2002.
V.V. Strelkov. A new similarity measure for histogram comparison and its application in time series analysis, Pattern Recognition Letters, Vol. 29, pp. 1768–1774, 2008.
Y.Rubner, C. Tomasi, and L. J. Guibas., The Earth Mover's Distance as a Metric for Image Retrieval, International Journal of Computer Vision, Vol. 40, No. 2, pp. 99-121, 2009.
Dr. Ali C. Gedik
Dokuz Eylul University - Turkey