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FFT-based features selection for Javanese music note and instrument identification using support vector machines

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4 Author(s)
Aris Tjahyanto ; Information Systems Department, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia ; Yoyon K Suprapto ; Mauridhi Hery Purnomo ; Diah Puspito Wulandari

Most automatic music transcription research is related with Western music, and still less for the Javanese gamelan music. In this paper, we proposed a method for the features extraction, selection, and identification of gamelan note and the proper instrument. It was an approach based on Fast Fourier Transform (FFT), and support vector machines (SVMs) for note and instrument identification. We selected four spectral features (spectral centroid, two spectral rolloff, and fundamental frequency) as input for SVM. Experimental results show that fundamental frequency, spectral centroid, and spectral rolloff can be used to distinguish gamelan instrument with accuracy or recognition rate more than 95%.

Published in:

Computer Science and Automation Engineering (CSAE), 2012 IEEE International Conference on  (Volume:1 )

Date of Conference:

25-27 May 2012