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International Conference on Artificial Intelligence and Soft Computing

ICAISC 2019: Artificial Intelligence and Soft Computing pp 542–552Cite as

Automatic Recognition of Melody Similarity

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11509))

Abstract

The problem of the automatic recognition of a melody similarity is considered. A special data set with a number of different artificial modifications of original melodies was created to test several classification algorithms. The best algorithm (J48) was chosen to carry out a wider analysis. The results showed that the melody similarity can be described mathematically.

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Author information

Authors and Affiliations

  1. Faculty of Philosophy, John Paul II Catholic University of Lublin, Al. Racławickie 14, 20-950, Lublin, Poland

    Tomasz Grȩbski & Piotr Kulicki

  2. Faculty of Mathematics and Natural Sciences, University of Rzeszów, Pigonia Street 1, 35-310, Rzeszów, Poland

    Krzysztof Pancerz

Authors
  1. Tomasz Grȩbski
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  2. Krzysztof Pancerz
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  3. Piotr Kulicki
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Corresponding author

Correspondence to Krzysztof Pancerz .

Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Częstochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Rafał Scherer

  3. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  4. University of Alberta, Edmonton, AB, Canada

    Witold Pedrycz

  5. AGH University of Science and Technology, Kraków, Poland

    Ryszard Tadeusiewicz

  6. University of Louisville, Louisville, KY, USA

    Jacek M. Zurada

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© 2019 Springer Nature Switzerland AG

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Cite this paper

Grȩbski, T., Pancerz, K., Kulicki, P. (2019). Automatic Recognition of Melody Similarity. In: Rutkowski, L., Scherer, R., Korytkowski, M., Pedrycz, W., Tadeusiewicz, R., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2019. Lecture Notes in Computer Science(), vol 11509. Springer, Cham. https://doi.org/10.1007/978-3-030-20915-5_48

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  • DOI: https://doi.org/10.1007/978-3-030-20915-5_48

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-20914-8

  • Online ISBN: 978-3-030-20915-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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