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Mehmet Ünal’s music carries forward the academic study by Barış Bozkurt, who targets a review of the computational analysis literature for Turkish Makam Music. Studies on tuning analysis, automatic transcription, automatic melodic analysis, automatic makam and usul detection are reviewed.


This graph presents examples from the graphics obtained as a result of the analysis of Tanburi Cemil Bey's recordings with the frequency distribution measurement technique presented in the article.

The term ‘makam’ mainly refers to a modality system and is used in many genres (Turkish traditional/classical/art music). The data sets used for Machine Learning include pieces from a time span of four centuries from composers like Itri, İsmail Dede Efendi, Hacı Arif Bey, Tanburi Cemil Bey and Sadettin Kaynak. By analyzing the 2,500 works of famous Turkish artists, the notes and frequencies they composed were extracted.

Training And Testing Data In Machine Learning
Computational Analysis Literature For Turkish Makam Music.

This data set was trained using the Markov Chain algorithm, named after Andrey Markov, which describes mathematical systems that create a probability of "transitioning," from one state (a situation or set of values) to another. It allows the Artificial Intelligence to produce new variations of Turkish makam music in melodic, rhythmic and timbral aspects, which are used in Ünal’s piece.

Within the frame of Turkish makam music, Mehmet Ünal’s work combines analysis of rhythmic and melodic aspects and adapts it to modern sonical aesthetics and different musical styles. This approach ties with Togg’s values of embracing heritage and culture, whilst adapting to state-of the art technologies.

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