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Human-Level Melodic Line Harmonization

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Computational Science – ICCS 2022 (ICCS 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13350))

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Abstract

This paper examines potential applicability and efficacy of Artificial Intelligence (AI) methods in automatic music generation. Specifically, we propose an Evolutionary Algorithm (EA) capable of constructing melodic line harmonization with given harmonic functions, based on the rules of music composing which are applied in the fitness function. It is expected that harmonizations constructed in accordance to these rules would be formally correct in terms of music theory and, additionally, would follow less-formalised aesthetic requirements and expectations. The fitness function is composed of several modules, with each module consisting of smaller parts. This design allows for its flexible modification and extension. The way the fitness function is constructed and tuned towards better quality harmonizations is discussed in the context of music theory and technical EA implementation. In particular, we show how could generated harmonizations be modelled by means of adjusting the relevance of particular fitness function components. The proposed method generates solutions which are technically correct (i.e. in line with music harmonization theory) and also “nice to listen to” (i.e. aesthetically plausible) as assessed by an expert - a harmony teacher.

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Author information

Authors and Affiliations

  1. Warsaw University of Technology, Warsaw, Poland

    Jan Mycka, Adam Żychowski & Jacek Mańdziuk

  2. AGH University of Science and Technology, Krakow, Poland

    Jacek Mańdziuk

Authors
  1. Jan Mycka
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  2. Adam Żychowski
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  3. Jacek Mańdziuk
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Corresponding author

Correspondence to Adam Żychowski .

Editor information

Editors and Affiliations

  1. Brunel University London, London, UK

    Derek Groen

  2. University of Amsterdam, Amsterdam, The Netherlands

    Clélia de Mulatier

  3. AGH University of Science and Technology, Krakow, Poland

    Maciej Paszynski

  4. University of Amsterdam, Amsterdam, The Netherlands

    Valeria V. Krzhizhanovskaya

  5. University of Tennessee at Knoxville, Knoxville, TN, USA

    Jack J. Dongarra

  6. University of Amsterdam, Amsterdam, The Netherlands

    Peter M. A. Sloot

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Mycka, J., Żychowski, A., Mańdziuk, J. (2022). Human-Level Melodic Line Harmonization. In: Groen, D., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M.A. (eds) Computational Science – ICCS 2022. ICCS 2022. Lecture Notes in Computer Science, vol 13350. Springer, Cham. https://doi.org/10.1007/978-3-031-08751-6_2

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  • DOI: https://doi.org/10.1007/978-3-031-08751-6_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-08750-9

  • Online ISBN: 978-3-031-08751-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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