top of page
  • Yazarın fotoğrafıCihan Işıkhan

Similarity Measurement for Plagiarism Detection in Turkish Music

Paper / Makale, 2020

Using a section or the whole of music without permission from its owner, plagiarism, is an undesirable situation frequently encountered in Turkish Music. Since plagiarism is not an act that can be accepted immediately, it can only be decided whether plagiarism has been committed or not when the similarity of music is examined. Contrary to the general belief that similarity can be determined with a subjective assessment based on perception, the primary target of this study is to show that similarity of Turkish Music can also be measured digitally. In this study, firstly, melody extraction using the techniques of musical analysis/structural reduction and pitch separation/section detection has been applied two Turkish Music that is supposed to be similar to each other due to the scenario. Secondly, the similarity value of extracted melodies of Turkish Music has been measured by using meldistance function. The first results in this study, which will be expanded and tested afterwards, show that the meldistance function and the method of similarity measurement in order to detect the plagiarism in Turkish Music are highly effective.
“Since plagiarism is not an act that can be accepted immediately, it can only be decided whether plagiarism has been committed or not when the similarity of music is examined.”


Amutha, P. N, Abhishek G., and Vidhyasagar G. (2019), Plagiarism Analysis in Musical Notes, International Journal of Recent Technology and Engineering (IJRTE), Vol. 8(1), May

Bhattacharya, M., Bandkar S., and Badala A. (2014), Music Analyzer and Plagiarism, International Journal of Research in Engineering and Technology (IJRET), Vol.3, Special Issue 5, May, pp.7-11

Bozkurt, B., Ayangil, R., and Holzapfel, A. (2014). Computational Analysis of Turkish Makam Music: Review of State-Of-The-Art and Challenges, Journal of New Music Research, Vol.43 (1), pp. 3-23

Bozkurt, B., Yarman, O., Karaosmanoğlu, M. K., and Akkoç, C. (2009). Weighing Diverse Theoretical Models on Turkish Maqam Music Against Pitch Measurements: A Comparison of Peaks Automatically Derived from Frequency Histograms With Proposed Scale Tones, Journal of New Music Research, Vol.38(1), pp.45-70

Dittmar, C., Hildebrand K. F., Gaertner D., Winges M., Muller F., and Aichroth P. (2012). Audio Forensics Meets Music Information Retrieval: A Toolbox for Inspection of Music Plagiarism, in Proceedings of the 20th European Signal Processing Conference (EUSIPCO), Bucharest, Romania, pp. 1249-1253

Eerola, T.&Toiviainen P. (2016), MIDI ToolBox for MATLAB, Manual Book,

Eerola, T. & Toiviainen P. (2004), MIR in Matlab: The Midi Toolbox, in Proc. of 5th International Symposium of Music Information Retrieval, pp. 22–27.

Gedik, A. C., & Bozkurt, B. (2010). Pitch-Frequency Histogram-Based Music Information Retrieval for Turkish Music, Signal Processing, Vol.90 (4), pp. 1049-1063.

Gedik, A. C & Bozkurt B. (2008). Automatic Classification of Turkish Traditional Art Music Recordings by Ariel Theory, In Proc. (online) of 4th Conference on Interdisciplinary Musicology, Thessaloniki, Greece.

Gao, P., You C. and Chi T. (2020). A Multi-Dilation and Multi-Resolution Fully Convolutional Network for Singing Melody Extraction, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Barcelona, Spain, pp. 551-555

Goto, M. (2004). A Real-Time Music-Scene-Description System: Predominantf0 Estimation for Detecting Melody and Bass Lines in Real-World Audio Signals, Speech Communication, Vol.43, pp.311-329

Hewlett, W. B.&Selfridge-Field, E. (1998). Melodic Similarity: Concepts, Procedures, And Applications (Computing in Musicology 11), The MIT Press

Holzapfel, A. & Stylianou, Y. (2009). Rhythmic Similarity in Traditional Turkish Music, In Proc. of International Conference on Music Information Retrieval, pp. 99-104

Işıkhan, C. (2018). MIDI Dönüştürücü Yazılımların Başarı Karşılaştırması ve MatLab'de Müzik Analizi, AKÜ Müzik Araştırmaları Dergisi (AMADER), Haziran, Cilt 4, Sayı 8, s. 1-11

Isikhan, C., & Ozcan, G. (2008). A Survey of Melody Extraction Techniques for Music Information Retrieval. In Proceeding (online) of 4th Conference on Interdisciplinary Musicology (CIM’08), Thessaloniki, Greece, pp. 2-8

Işıkhan, C. (2006). Dizi Temelli Ezgi Karşılaştırma: Algısal Perde Hiyerarşisinde Tonal-Diyatonik Ayrımı, Doktora Tezi, Danışman: Prof. Dr. Yetkin Özer, Yard. Doç. Dr. Adil Alpkoçak, Müzik Bilimleri Anabilimdalı, Güzel Sanatlar Enstitüsü, Dokuz Eylül Üniversitesi

Karaosmanoglu, M. K. (2012). A Turkish Makam Music Symbolic Database for Music Information Retrieval: Symbtr, In Proceedings of 13th International Society for Music Information Retrieval Conference; Porto, Portugal, pp. 223-228

Lee J., Park S., Jo S., and Yoo C. D. (2011). Music Plagiarism Detection System, in Proceedings of the 26th International Technical Conference on Circuits/Systems, Computers and Communications, Gyeongju, Korea, pp. 828-830

Li L., Junwei C., Lei W., and Yan M. (2008). Melody Extraction from Polyphonic MIDI Files Based on Melody Similarity, in Proceedings of the International Symposium on Information Science and Engineering, Vol. 2, pp. 232-235.

McKay C., Cumming J. E., and Fujinaga I., (2018). Jsymbolic 2.2: Extracting Features from Symbolic Music for Use in Musicological and MIR Research, in Proc. of the 19th ISMIR Conference, France, Paris, September, pp.23-27

Mongeau, M. & Sankoff, D. (1990). Comparison of Musical Sequences, Computers and the Humanities, Vol. 24, pp. 161-175

Orio N. (2006). Music Retrieval: A Tutorial and Review, Foundations and Trends in Information Retrieval, V1 (1), pp-1-90

Ozcan, G., Isikhan C., and Alpkocak, A. (2005). Melody Extraction on MIDI Music Files, In Proc. of 7th IEEE International Symposium on Multimedia (ISM’05), Irvine, USA, pp. 8-17

Paiva, R. P., Mendes T., and Cardoso A. (2006). Melody Detection in Polyphonic Musical Signals: Exploiting Perceptual Rules, Note Salience, and Melodic Smoothness, Computer Music Journal, Vol.30 (4), Winter, pp. 80-98

Park, M.W., & Lee, E. (2013). Similarity Measurement Method between Two Songs by Using the Conditional Euclidean Distance, WSEAS Transactions on Information Science and Applications, Vol. 10, No. 12, pp. 381-388

Parncutt R. (1994). A Perceptual Model of Pulse Salience and Metrical Accent in Musical Rhythms, Music Perception, Vol.11 (4), pp. 409-464

Pitt, I. L. (2010). Economic Analysis of Music Copyright: Income, Media and Performances, Springer Science & Business Media Poliner G. E., Ellis D. P. W., Ehmann F., Gómez E., Streich S., and Ong B. (2007), Melody Transcription from Music Audio: Approaches and Evaluation, IEEE Trans. Audio, Speech, Lang. Processing, Vol. 15, No. 4, pp. 1247–1256

Rosen, R. S. (2008), Music and Copyright, Oxford University Press

Salamon J.& Urbano J. (2012). Current Challenges in The Evaluation of Predominant Melody Extraction Algorithms, In Proceedings of International Society for Music Information Retrieval Conference, October, Porto, Portugal, pp. 289–294

Salamon, J., & Gómez, E. (2012). Melody Extraction from Polyphonic Music Signals Using Pitch Contour Characteristics, IEEE Transactions on Audio, Speech and Language Processing, Vol.20, No. 6, pp. 1759-1770

Salamon, J., Gómez, E., Ellis, D. P., & Richard, G. (2014). Melody Extraction from Polyphonic Music Signals: Approaches, Applications, and Challenges, IEEE Signal Processing Magazine, Vol.31(2), pp. 118-134.

Saracoglu A., Esen E., Ates T. K., Acar B. O., Zubari U., Ozan E. C., Ozalp E., Alatan A. A., and Ciloglu T. (2009). Content Based Copy Detection with Coarse Audio-Visual Fingerprints, in Proceedings of the 7th International Workshop on Content-Based Multimedia Indexing, June, IEEE, pp. 213-218

Schedl, M., Gómez G. E., and Urbano, J. (2014). Music Information Retrieval: Recent Developments and Applications, Foundations and Trends in Information Retrieval, Sept 12, V.8 (2-3), pp. 127-261

Shih H. H., Narayanan S. S., and Kuo C. J. (2001). Automatic Main Melody Extraction from MIDI Files with A Modified Lempel-Ziv Algorithm, in Proceedings of the 2001 International Symposium on Intelligent Multimedia, Video and Speech Processing, pp. 9-12.

Şentürk, S., Ferraro, A., Porter, A., and Serra, X. (2015). A Tool for The Analysis and Discovery of Ottoman-Turkish Makam Music, Extended abstracts for the Late Breaking Demo Session of the 16th International Society for Music Information Retrieval Conference, pp. 687–693

Typke, R., Wiering, F., and Veltkamp, R. C. (2005). A Survey of Music Information Retrieval Systems, In Proc. of 6th International Conference on Music Information Retrieval, University of London, pp. 153-160

Uitdenbogerd, A. & Zobel, J. (1999). Melodic Matching Techniques for Large Music Databases. In Proceedings of 7th International Multimedia Conference (ACM), Part I, pp. 57-66

Yıldırım, O. M. (2020). Bilgisayar Tabanlı Müzik Analizinde MIDI ToolBox Kullanımı, Yüksek Lisans Tezi, Danışman: Prof. Dr. Cihan Işıkhan, Müzik Teknolojisi Bilimdalı, Güzel Sanatlar Enstitüsü, Dokuz Eylül Üniversitesi

11 görüntüleme0 yorum


bottom of page