Evaluating Feature Selection Algorithms for Machine Learning-Based Musical Instrument Identification in Monophonic Recordings

İsmet Emre Yücel; Ulaş Yurtsever

doi:10.35377/saucis...1516717

EN

Evaluating Feature Selection Algorithms for Machine Learning-Based Musical Instrument Identification in Monophonic Recordings

Abstract

Musical instrument identification (MII) research has been studied as a subfield of the Music Information Retrieval (MIR) field. Conventional MII models are developed based on hierarchical models representing musical instrument families. However, for MII models to be used in the field of music production, they should be developed based on the arrangement-based functions of instruments in musical styles rather than these hierarchical models. This study investigates how the performance of machine learning based classification algorithms for Guitar, Bass guitar and Drum classes changes with different feature selection algorithms, considering a popular music production scenario. To determine the effect of feature statistics on model performance, Minimum Redundancy Maximum Relevance (mRMR), Chi-sqaure (Chi2), ReliefF, Analysis of Variance (ANOVA) and Kruskal Wallis feature selection algorithms were used. In the end, the neural network algorithm with wide hyperparameters (WNN) achieved the best classification accuracy (91.4%) when using the first 20 statistics suggested by the mRMR and ReliefF feature selection algorithms.

Keywords

References

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Details

Primary Language

English

Subjects

Software Engineering (Other)

Journal Section

Research Article

Authors

İsmet Emre Yücel ^*
0000-0001-7018-3349
Türkiye

Ulaş Yurtsever
0000-0003-3438-6872
Türkiye

Early Pub Date

August 27, 2024

Publication Date

August 31, 2024

Submission Date

July 15, 2024

Acceptance Date

August 21, 2024

Published in Issue

Year 2024 Volume: 7 Number: 2

DOI

https://doi.org/10.35377/saucis...1516717

IZ

https://izlik.org/JA44HX69LX

Cite

RIS / Bibtex

APA

Yücel, İ. E., & Yurtsever, U. (2024). Evaluating Feature Selection Algorithms for Machine Learning-Based Musical Instrument Identification in Monophonic Recordings. Sakarya University Journal of Computer and Information Sciences, 7(2), 289-301. https://doi.org/10.35377/saucis...1516717

AMA

1.Yücel İE, Yurtsever U. Evaluating Feature Selection Algorithms for Machine Learning-Based Musical Instrument Identification in Monophonic Recordings. SAUCIS. 2024;7(2):289-301. doi:10.35377/saucis.1516717

Chicago

Yücel, İsmet Emre, and Ulaş Yurtsever. 2024. “Evaluating Feature Selection Algorithms for Machine Learning-Based Musical Instrument Identification in Monophonic Recordings”. Sakarya University Journal of Computer and Information Sciences 7 (2): 289-301. https://doi.org/10.35377/saucis. 1516717.

EndNote

Yücel İE, Yurtsever U (August 1, 2024) Evaluating Feature Selection Algorithms for Machine Learning-Based Musical Instrument Identification in Monophonic Recordings. Sakarya University Journal of Computer and Information Sciences 7 2 289–301.

IEEE

[1]İ. E. Yücel and U. Yurtsever, “Evaluating Feature Selection Algorithms for Machine Learning-Based Musical Instrument Identification in Monophonic Recordings”, SAUCIS, vol. 7, no. 2, pp. 289–301, Aug. 2024, doi: 10.35377/saucis...1516717.

ISNAD

Yücel, İsmet Emre - Yurtsever, Ulaş. “Evaluating Feature Selection Algorithms for Machine Learning-Based Musical Instrument Identification in Monophonic Recordings”. Sakarya University Journal of Computer and Information Sciences 7/2 (August 1, 2024): 289-301. https://doi.org/10.35377/saucis. 1516717.

JAMA

1.Yücel İE, Yurtsever U. Evaluating Feature Selection Algorithms for Machine Learning-Based Musical Instrument Identification in Monophonic Recordings. SAUCIS. 2024;7:289–301.

MLA

Yücel, İsmet Emre, and Ulaş Yurtsever. “Evaluating Feature Selection Algorithms for Machine Learning-Based Musical Instrument Identification in Monophonic Recordings”. Sakarya University Journal of Computer and Information Sciences, vol. 7, no. 2, Aug. 2024, pp. 289-01, doi:10.35377/saucis. 1516717.

Vancouver

1.İsmet Emre Yücel, Ulaş Yurtsever. Evaluating Feature Selection Algorithms for Machine Learning-Based Musical Instrument Identification in Monophonic Recordings. SAUCIS. 2024 Aug. 1;7(2):289-301. doi:10.35377/saucis. 1516717