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Music Genre Classification Revisited: An In-Depth Examination Guided by Music Experts

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Music Technology with Swing (CMMR 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11265))

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Abstract

Despite their many identified shortcomings, music genres are still often used as ground truth and as a proxy for music similarity. In this work we therefore take another in-depth look at genre classification, this time with the help of music experts. In comparison to existing work, we aim at including the viewpoint of different stakeholders to investigate whether musicians and end-user music taxonomies agree on genre ground truth, through a user study among 20 professional and semi-professional music protagonists. We then compare the results of their genre judgments with different commercial taxonomies and with that of computational genre classification experiments, and discuss individual cases in detail. Our findings coincide with existing work and provide further evidence that a simple classification taxonomy is insufficient.

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Notes

  1. 1.

    George Tzanetakis, the author of the dataset, has repeatedly confirmed being aware of these issues, but has chosen not to correct them since the dataset has been used so many times and changing the files would render comparisons of results infeasible.

  2. 2.

    The genre “classical” was included even though no track was classified as such.

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Acknowledgements

Supported by the Austrian Science Fund (FWF): P25655 and the Austrian FFG: BRIDGE 1 project SmarterJam (858514).

Author information

Authors and Affiliations

  1. Reykjavik University, Reykjavík, Iceland

    Haukur Pálmason & Björn Þór Jónsson

  2. IT University of Copenhagen, Copenhagen, Denmark

    Björn Þór Jónsson

  3. Johannes Kepler University Linz, Linz, Austria

    Markus Schedl

  4. TU Wien, Vienna, Austria

    Peter Knees

Authors
  1. Haukur Pálmason
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  2. Björn Þór Jónsson
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  3. Markus Schedl
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  4. Peter Knees
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Corresponding author

Correspondence to Peter Knees .

Editor information

Editors and Affiliations

  1. Laboratoire PRISM, AMU-CNRS, Marseille, France

    Mitsuko Aramaki

  2. INESC TEC, Porto, Portugal

    Matthew E. P. Davies

  3. Laboratoire PRISM, AMU-CNRS, Marseille, France

    Richard Kronland-Martinet

  4. Laboratoire PRISM, AMU-CNRS, Marseille, France

    Sølvi Ystad

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Pálmason, H., Jónsson, B.Þ., Schedl, M., Knees, P. (2018). Music Genre Classification Revisited: An In-Depth Examination Guided by Music Experts. In: Aramaki, M., Davies , M., Kronland-Martinet, R., Ystad, S. (eds) Music Technology with Swing. CMMR 2017. Lecture Notes in Computer Science(), vol 11265. Springer, Cham. https://doi.org/10.1007/978-3-030-01692-0_4

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  • DOI: https://doi.org/10.1007/978-3-030-01692-0_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-01691-3

  • Online ISBN: 978-3-030-01692-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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