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All Journal Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Computer Science Prosiding Simposium Nasional Rekayasa Aplikasi Perancangan dan Industri
Rifai Chai
Swinburne University of Technology
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Electrical & Electronics Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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Journal : Bulletin of Electrical Engineering and Informatics

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DCT based feature extraction and support vector machine classification for musical instruments tone recognition Linggo Sumarno; Rifai Chai
Bulletin of Electrical Engineering and Informatics Vol 10, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i5.3158

Abstract

The conducted research proposes a feature extraction and classification combination method that is used in a tone recognition system for musical instruments. It is expected that by implementing this combination, the tone recognition system will require fewer feature extraction coefficients than those previously investigated. The proposed combination comprises of feature extraction using discrete cosine transform (DCT) and classification using support vector machine (SVM). Bellyra, clarinet, and pianica tones were used in the experiment, with each indicating a tone with one, several, or many major local peaks in the transform domain. Based on the results of the tests, the proposed combination is efficient enough to be used in a tone recognition system for musical instruments. This is indicated in recognizing a tone, it only needs at least eight feature extraction coefficients.
Co-Authors Alfian Pramudita Putra Henry Candra Jeanny Pragantha Khouliya Zalda Khusnul Ain Linggo Sumarno Nafisa Rahmatul Laili Alami Nita Lutfiyah Osmalina Nur Rahma Riries Rulaningtyas Setyaningsih, Endah