Feature-Based Classification of Electric Guitar Types

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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.

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de Castro Rabelo Profeta, R., & Schuller, G. (2020). Feature-Based Classification of Electric Guitar Types. In Communications in Computer and Information Science (Vol. 1168 CCIS, pp. 478–484). Springer. https://doi.org/10.1007/978-3-030-43887-6_41

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