| Recommended Reading List |
Karaosmanoğlu, M. K. (2015). Türk Musikisi sembolik verileri üzerinde hesaplamalı ezgi analizi; Bozkurt, B., Karaçalı, B., Karaosmanoğlu, M. K., & Ünal, E. (2014). Türk makam müziği notaları için otomatik ezgi bölütleme. In 2014 22nd Signal Processing and Communications Applications Conference, SIU 2014-Proceedings. Institute of Electrical and Electronics Engineers Inc.; Atlı, H. S., & Bozkurt, B. (2015, May). Automatic tonic identification method for Turkish makam music. In 2015 23nd Signal Processing and Communications Applications Conference (SIU) (pp. 1570-1573). IEEE.; Bozkurt, B., Savacı, F. A., & Karaosmanoğlu, M. K. (2010). Klasik Türk Müziği kayıtlarının otomatik olarak notaya dökülmesi ve otomatik makam tanıma.; Karaosmanoğlu, M. K., Berkman, E., & Berkman, M. İ. (2023). Examining transposed makams in Turkish music through machine learning: classification of Rengidil-Neveser and Ruhnevaz-Buselik pieces. Journal of New Music Research, 1-15. |
| Catalog Content |
Maqam Recognition Studies with Computational Methods: Models of pitch analysis, Implementing the auditory datas to maqam-based analysis, Correctness of maqam theories according to pitch measurements, New approaches in computational analysis of Turkish maqam music, Computational approaches to compilation techniques, Computational analysis techniques applied to maqam analysis, Determining the theoretical and practical differences of maqam music instruments with computational techniques, Transcriptions of Taksim recordings. |
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