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2018 | OriginalPaper | Chapter

The Classification of Music by the Genre Using the KNN Classifier

Authors : Daniel Kostrzewa, Robert Brzeski, Maciej Kubanski

Published in: Beyond Databases, Architectures and Structures. Facing the Challenges of Data Proliferation and Growing Variety

Publisher: Springer International Publishing

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Abstract

The article presents the possibility of classifying music tracks according to their musical genre. This issue is interesting because it is difficult to find solutions that look for similarity between songs based on their waveforms, as in this work. This article shows that such a classification is possible. For this process, the KNN classifier was used, for which it is possible to apply different metrics (metric spaces). The article shows the validity of testing different distance measures in the classification process. The analysis of music tracks and assignment to the appropriate genre is carried out, on the basis of attributes describing the music track. These attributes are obtained using the jAudio library. The development of further research in this area may allow finding other suitable music not only on the basis of historical data about the user (what he was listening to along with the music track) but also directly on the basis of the genre of the given song.

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Title: The Classification of Music by the Genre Using the KNN Classifier
Authors: Daniel Kostrzewa
Robert Brzeski
Maciej Kubanski
Publisher: Springer International Publishing
Book: Beyond Databases, Architectures and Structures. Facing the Challenges of Data Proliferation and Growing Variety
Print ISBN: 978-3-319-99986-9

Electronic ISBN: 978-3-319-99987-6

Copyright Year: 2018
DOI: https://doi.org/10.1007/978-3-319-99987-6_18

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