Artificial Intelligence-Based Classification with Classical Turkish Music Makams: Possibilities to Turkish Music Education

Autor/inn/en	Kayis, Mert; Hardalaç, Naciye; Ural, A. Berkan; Hardalaç, Firat
Titel	Artificial Intelligence-Based Classification with Classical Turkish Music Makams: Possibilities to Turkish Music Education
Quelle	In: African Educational Research Journal, 9 (2021) 2, S.570-580 (11 Seiten) PDF als Volltext kostenfreie Datei Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	2354-2160
Schlagwörter	Foreign Countries; Folk Culture; Music Education; Classification; Artificial Intelligence; Educational Technology; Musical Composition; Music Theory; Musical Instruments; Acoustics; Turkey + Suchen Sie Ihr Suchwort? Ausland; Musikerziehung; Classification system; Klassifikation; Klassifikationssystem; Künstliche Intelligenz; Unterrichtsmedien; Komponieren; Musiktheorie; Musikinstrument; Akustik; Türkei
Abstract	Makams of Classical Turkish Music have been tried to be classified through various studies for the past years. Significant differences of opinion have emerged in the classification process of the makams in Music Education and Literacy from past to present. This situation creates problems in learning the makams related to music education and recognizing the makams heard. Additionally, there are uncertainties in the classification of the makam genre of the song, as individual mistakes were made while notating the musical notes. Apart from that, this situation constitutes a problem not only for the ones studying Turkish Classical Music but also for the ones interested in this certain type of Music. Therefore, the objective of the research is to contribute to the makam classification in Classical Turkish Music Education by developing an MIR system that determines the makam of the songs. Theoretically, we can extract the properties of sound signals with Time Wavelet Scattering Feature Extraction, classify them with SVM and distinguish between types of makams. In this study, upon eight different Makams, a Musical Information Retrieval system has been created via the Artificial Intelligence (AI) method of Support Vector Machines (SVM) and Time Wavelet Scattering Feature Extraction and through using a Graphics Processing Unit (GPU) accelerator for the sake of feature extraction. We performed the classification process by modeling it on the MATLAB program. The study's success rate was identified as 98.21% and it acquired a higher success rate compared to the other studies in the literature. After completing the classification procedure, the Makams were identified by sending samples belonging to different sound files from the system consisting of a database belonging to eight different Makams. In our study, the classification and detection processes were realized with nearly a hundred percent success. The difficulties encountered in classifying the makams in Classical Turkish Music mentioned above, with the application of artificial intelligence, the classification difficulty of individuals who have received this type of training or are interested in this subject has been overcome. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01