The classification of music by the genre using the KNN classifier

Daniel Kostrzewa; Robert Brzeski; Maciej Kubanski

doi:10.1007/978-3-319-99987-6_18

The classification of music by the genre using the KNN classifier

Daniel Kostrzewa
, Robert Brzeski
, Maciej Kubanski

Department of Applied Informatics (RAU/RAU7)

Silesian University of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

11 Citations (Scopus)

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.

Original language	English
Title of host publication	Beyond Databases, Architectures and Structures. Facing the Challenges of Data Proliferation and Growing Variety - 14th International Conference, BDAS 2018, Held at the 24th IFIP World Computer Congress, WCC 2018, Proceedings
Editors	Stanislaw Kozielski, Dariusz Mrozek, Pawel Kasprowski, Bozena Malysiak-Mrozek, Daniel Kostrzewa
Publisher	Springer Verlag
Pages	233-242
Number of pages	10
ISBN (Print)	9783319999869
DOIs	https://doi.org/10.1007/978-3-319-99987-6_18
Publication status	Published - 2018
Event	14th International Conference on Beyond Databases, Architectures and Structures, BDAS 2018 Held at the 24th IFIP World Computer Congress, WCC 2018 - Poznan, Poland Duration: 18 Sept 2018 → 20 Sept 2018

Publication series

Name	Communications in Computer and Information Science
Volume	928
ISSN (Print)	1865-0929

Conference

Conference	14th International Conference on Beyond Databases, Architectures and Structures, BDAS 2018 Held at the 24th IFIP World Computer Congress, WCC 2018
Country/Territory	Poland
City	Poznan
Period	18/09/18 → 20/09/18

Keywords

Accuracy
Classification
KNN
Kappa
Metric
Music genre
Music track
Song
jAudio

ASJC Scopus subject areas

General Computer Science
General Mathematics

Access to Document

10.1007/978-3-319-99987-6_18

Cite this

Kostrzewa, D., Brzeski, R., & Kubanski, M. (2018). The classification of music by the genre using the KNN classifier. In S. Kozielski, D. Mrozek, P. Kasprowski, B. Malysiak-Mrozek, & D. Kostrzewa (Eds.), Beyond Databases, Architectures and Structures. Facing the Challenges of Data Proliferation and Growing Variety - 14th International Conference, BDAS 2018, Held at the 24th IFIP World Computer Congress, WCC 2018, Proceedings (pp. 233-242). (Communications in Computer and Information Science; Vol. 928). Springer Verlag. https://doi.org/10.1007/978-3-319-99987-6_18

Kostrzewa, Daniel ; Brzeski, Robert ; Kubanski, Maciej. / The classification of music by the genre using the KNN classifier. Beyond Databases, Architectures and Structures. Facing the Challenges of Data Proliferation and Growing Variety - 14th International Conference, BDAS 2018, Held at the 24th IFIP World Computer Congress, WCC 2018, Proceedings. editor / Stanislaw Kozielski ; Dariusz Mrozek ; Pawel Kasprowski ; Bozena Malysiak-Mrozek ; Daniel Kostrzewa. Springer Verlag, 2018. pp. 233-242 (Communications in Computer and Information Science).

@inproceedings{73680bf9a86c44f399628bde9ecec7f7,

title = "The classification of music by the genre using the KNN classifier",

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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author = "Daniel Kostrzewa and Robert Brzeski and Maciej Kubanski",

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Kostrzewa, D , Brzeski, R & Kubanski, M 2018, The classification of music by the genre using the KNN classifier. in S Kozielski, D Mrozek, P Kasprowski, B Malysiak-Mrozek & D Kostrzewa (eds), Beyond Databases, Architectures and Structures. Facing the Challenges of Data Proliferation and Growing Variety - 14th International Conference, BDAS 2018, Held at the 24th IFIP World Computer Congress, WCC 2018, Proceedings. Communications in Computer and Information Science, vol. 928, Springer Verlag, pp. 233-242, 14th International Conference on Beyond Databases, Architectures and Structures, BDAS 2018 Held at the 24th IFIP World Computer Congress, WCC 2018, Poznan, Poland, 18/09/18. https://doi.org/10.1007/978-3-319-99987-6_18

The classification of music by the genre using the KNN classifier. / Kostrzewa, Daniel ; Brzeski, Robert; Kubanski, Maciej.
Beyond Databases, Architectures and Structures. Facing the Challenges of Data Proliferation and Growing Variety - 14th International Conference, BDAS 2018, Held at the 24th IFIP World Computer Congress, WCC 2018, Proceedings. ed. / Stanislaw Kozielski; Dariusz Mrozek; Pawel Kasprowski; Bozena Malysiak-Mrozek; Daniel Kostrzewa. Springer Verlag, 2018. p. 233-242 (Communications in Computer and Information Science; Vol. 928).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - The classification of music by the genre using the KNN classifier

AU - Kostrzewa, Daniel

AU - Brzeski, Robert

AU - Kubanski, Maciej

N1 - Publisher Copyright: © Springer Nature Switzerland AG 2018.

PY - 2018

Y1 - 2018

N2 - 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.

AB - 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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KW - KNN

KW - Kappa

KW - Metric

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KW - Music track

KW - Song

KW - jAudio

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DO - 10.1007/978-3-319-99987-6_18

M3 - Conference contribution

AN - SCOPUS:85053832532

SN - 9783319999869

T3 - Communications in Computer and Information Science

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EP - 242

BT - Beyond Databases, Architectures and Structures. Facing the Challenges of Data Proliferation and Growing Variety - 14th International Conference, BDAS 2018, Held at the 24th IFIP World Computer Congress, WCC 2018, Proceedings

A2 - Kozielski, Stanislaw

A2 - Mrozek, Dariusz

A2 - Kasprowski, Pawel

A2 - Malysiak-Mrozek, Bozena

A2 - Kostrzewa, Daniel

PB - Springer Verlag

T2 - 14th International Conference on Beyond Databases, Architectures and Structures, BDAS 2018 Held at the 24th IFIP World Computer Congress, WCC 2018

Y2 - 18 September 2018 through 20 September 2018

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Kostrzewa D , Brzeski R, Kubanski M. The classification of music by the genre using the KNN classifier. In Kozielski S, Mrozek D, Kasprowski P, Malysiak-Mrozek B, Kostrzewa D, editors, Beyond Databases, Architectures and Structures. Facing the Challenges of Data Proliferation and Growing Variety - 14th International Conference, BDAS 2018, Held at the 24th IFIP World Computer Congress, WCC 2018, Proceedings. Springer Verlag. 2018. p. 233-242. (Communications in Computer and Information Science). doi: 10.1007/978-3-319-99987-6_18

The classification of music by the genre using the KNN classifier

Abstract

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Keywords

ASJC Scopus subject areas

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