Turkish Journal of Electrical Engineering and Computer Sciences
Abstract
In this paper, we introduce a new deep-learning-based system that can compose structured Turkish makam music (TMM) in the symbolic domain. Presented artificial TMM composer (ATMMC) takes eight initial notes from a human user and completes the rest of the piece. The backbone of the composer system consists of multilayered long short-term memory (LSTM) networks. ATMMC can create pieces in Hicaz and Nihavent makams in Şarkı form, which can be viewed and played with Mus2, a notation software for microtonal music. Statistical analysis shows that pieces composed by ATMMC are approximately 84% similar to training data. ATMMC is an open-source project and can assist Turkish makam music enthusiasts with creating new pieces for professional, educational, or entertainment purposes.
DOI
10.3906/elk-2101-44
Keywords
Turkish makam music, automatic composition, deep learning, machine learning
First Page
3107
Last Page
3118
Recommended Citation
PARLAK, İ. H, ÇEBİ, Y, IŞIKHAN, C, & BİRANT, D (2021). Deep learning for Turkish makam music composition. Turkish Journal of Electrical Engineering and Computer Sciences 29 (7): 3107-3118. https://doi.org/10.3906/elk-2101-44
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