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All Journal International Journal of Electrical and Computer Engineering
Muhammad Nezar Mahardika
Institut Teknologi Sepuluh Nopember
Computer Science & IT Electrical & Electronics Engineering

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Music fingerprinting based on bhattacharya distance for song and cover song recognition Riyanarto Sarno; Dedy Rahman Wijaya; Muhammad Nezar Mahardika
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 2: April 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (452.327 KB) | DOI: 10.11591/ijece.v9i2.pp1036-1044

Abstract

People often have trouble recognizing a song especially, if the song is sung by a not original artist which is called cover song. Hence, an identification system might be used to help recognize a song or to detect copyright violation. In this study, we try to recognize a song and a cover song by using the fingerprint of the song represented by features extracted from MPEG-7. The fingerprint of the song is represented by Audio Signature Type. Moreover, the fingerprint of the cover song is represented by Audio Spectrum Flatness and Audio Spectrum Projection. Furthermore, we propose a sliding algorithm and k-Nearest Neighbor (k-NN) with Bhattacharyya distance for song recognition and cover song recognition. The results of this experiment show that the proposed fingerprint technique has an accuracy of 100% for song recognition and an accuracy of 85.3% for cover song recognition.
Co-Authors Dedy Rahman Wijaya Riyanarto Sarno