AI based algorithms for the detection of (ir)regularity in musical structure

• Autorzy: Mihelač Lorena , Povh Janez

Identyfikatory

DOI

10.34768/amcs-2020-0056

• Języki publikacji: EN

Abstrakty

EN

Regularity in musical structure is experienced as a strongly structured texture with repeated and periodic patterns, with the musical ideas presented in an appreciable shape to the human mind. We recently showed that manipulation of musical content (i.e., deviation of musical structure) affects the perception of music. These deviations were detected by musical experts, and the musical pieces containing them were labelled as irregular. In this study, we replace the human expert involved in detection of (ir)regularity with artificial intelligence algorithms. We evaluated eight variables measuring entropy and information content, which can be analysed for each musical piece using the computational model called Information Dynamics of Music and different viewpoints. The algorithm was tested using 160 musical excerpts. A preliminary statistical analysis indicated that three of the eight variables were significant predictors of regularity (E_cpitch, IC_cpintfref, and E_cpintfref). Additionally, we observed linear separation between regular and irregular excerpts; therefore, we employed support vector machine and artificial neural network (ANN) algorithms with a linear kernel and a linear activation function, respectively, to predict regularity. The final algorithms were capable of predicting regularity with an accuracy ranging from 89% for the ANN algorithm using only the most significant predictor to 100% for the ANN algorithm using all eight prediction variables.

Słowa kluczowe

EN

musical structure regularity; perception; AI algorithms

• Wydawca: Oficyna Wydawnicza Uniwersytetu Zielonogórskiego
• Czasopismo: International Journal of Applied Mathematics and Computer Science
• Rocznik: 2020
• Tom: Vol. 30, no. 4
• Strony: 761--772
• Opis fizyczny: Bibliogr. 75 poz., rys., tab., wykr.

Twórcy

autor

Mihelač Lorena

• SciDrom Scientific Lab, School Center Novo Mesto, Šegova ulica 112, 8000 Novo Mesto, Slovenia

autor

Povh Janez

• Faculty of Mechanical Engineering, University of Ljubljana, Aškerčeva ulica 6, 1000 Ljubljana, Slovenia; Institute of Mathematics, Physics and Mechanics, Jadranska ulica 19, 1000 Ljubljana, Slovenia

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