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Feature-Based Classification of Electric Guitar Types

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Part of the Communications in Computer and Information Science book series (CCIS,volume 1168)

Abstract

The classification of musical instruments of instruments of the same type is a challenging case of study. In this paper we conduct feature-based machine learning experiments to classify electric guitar recordings from different manufacturers and models. The Constant-Q Transform features and the Support Vector Machine algorithm obtained an accuracy of 95% in a binary classification task of guitars from two manufacturers, and 78% in a multiclass problem with four classes, distinguishing specific models from two different manufacturers.

Keywords

  • Musical instruments classification
  • Machine learning
  • Electric guitars
  • Music information retrieval

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  • DOI: 10.1007/978-3-030-43887-6_41
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Correspondence to Renato de Castro Rabelo Profeta .

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de Castro Rabelo Profeta, R., Schuller, G. (2020). Feature-Based Classification of Electric Guitar Types. In: Cellier, P., Driessens, K. (eds) Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2019. Communications in Computer and Information Science, vol 1168. Springer, Cham. https://doi.org/10.1007/978-3-030-43887-6_41

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  • DOI: https://doi.org/10.1007/978-3-030-43887-6_41

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-43886-9

  • Online ISBN: 978-3-030-43887-6

  • eBook Packages: Computer ScienceComputer Science (R0)