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An intelligent multi-agent system to create and classify fractal music

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Abstract

Even though it is known that music enacts emotional responses, computational systems aimed at creating music do not fully integrate them to generate or classify new musical pieces. This lack of integration represents an opportunity to discover patterns for the creation of new pieces and to predict which emotion is enacted by computer-created music. In this context we present an intelligent multi-agent system whose purpose is to create and classify fractal music according to the sixteen emotional categories in the Circumplex Model of Affect developed by Russell. The method of music creation relies on information fusion and the calculation of two validity indices to discover knowledge from the best clusters. Complementary to the creation of musical pieces, an ensemble of classifiers predicts the emotional response provoked by newly created pieces. Both modules rely on a psychoacoustics dataset to discover and classify new input values. Confirmatory results indicate that from one-hundred and forty-four musical pieces, altogether created to induce sixteen emotions, the classification module predicts the proper emotion in seventy-three percent of the cases. Accurately predicted cases are incorporated into the original dataset as new observations.

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Authors and Affiliations

  1. Área Académica de Sistemas Computacionales, Universidad Autónoma del Estado de Hidalgo, Carretera Pachuca-Tulancingo, km. 4.5, C. U., C. P. 42084, Pachuca, Hidalgo, Mexico

    Omar López-Ortega, Félix Castro-Espinoza & Obed Pérez-Cortés

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  1. Omar López-Ortega
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  2. Félix Castro-Espinoza
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  3. Obed Pérez-Cortés
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Correspondence to Omar López-Ortega.

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López-Ortega, O., Castro-Espinoza, F. & Pérez-Cortés, O. An intelligent multi-agent system to create and classify fractal music. Computing 100, 671–688 (2018). https://doi.org/10.1007/s00607-017-0584-3

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  • DOI: https://doi.org/10.1007/s00607-017-0584-3

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