Traditional Music Regional Classification using Convolutional Neural Network (CNN)

https://doi.org/10.22146/ijccs.73910

Raymond Luis(1*), Nur Rokhman(2)

(1) Bachelor Program of Computer Science, FMIPA UGM, Yogyakarta
(2) Department of Computer Science and Electronics, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada, Yogyakarta
(*) Corresponding Author

Abstract


Traditional Indonesian music is an Indonesian cultural heritage that is often forgotten by modern society. Many people do not know which area the traditional music came from. This is a problem because of the large amount of traditional music that loses its identity. Deep Learning technology can be a solution to this traditional music classification problem. The topic of traditional music classification was chosen because there has been no research using this topic before.

This research will classify traditional music based on the area of origin using data from Youtube with the extraction method of the Mel-Frequency Cepstral Coefficients (MFCC) feature and the Convolutional Neural Network (CNN) classification model. There are 7 provinces that will be used as classification labels, namely Riau, Papua, Special Capital District of Jakarta, Special Region of Yogyakarta , North Sumatra, West Java, and South Sulawesi.

The classification system produced in this study produced good classification accuracy with a value of 74.03%.


Keywords


Traditional Music; Audio Classification; Convolutional Neural Network; CNN; Mel-Frequency Cepstral Coefficients

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References

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DOI: https://doi.org/10.22146/ijccs.73910

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