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The article shows the potential of structural harmony method application in deep learning models training. Harmonic sequences, being represented as the paths in the system of graphs and then schematised, serve as the source of the deep learning models input. The visual character of the dataset generated using schemes allows the application of supervised machine learning technics and is suitable for time series analysis. Therefore, two neural network architectures – Convolutional and Convolutional Long-Short Term Memory were tested on example of music by postmodern composers Valentyn Sylvestrov (represented by vocal cycle “Silent songs”) and Philipp Glass (represented by piano cycle “Metamorphosis”).

Structural Harmony Method in the Context of Deep Learning on Example of Music by Valentyn Sylvestrov and Philipp Glass