International Journal of Electrical and Computer Engineering (IJECE) Vol. 9, No. 2, April 2019, pp. 1036~1044 ISSN: 2088-8708, DOI: 10.11591/ijece.v9i2.pp1036-1044  1036 Journal homepage: http://iaescore.com/journals/index.php/IJECE Music fingerprinting based on bhattacharya distance for song and cover song recognition Riyanarto Sarno 1 , Dedy Rahman Wijaya 2 , Muhammad Nezar Mahardika 3 1,2,3 Informatics Department, Institut Teknologi Sepuluh Nopember, Indonesia 2 School of Applied Science, Telkom University, Indonesia Article Info ABSTRACT Article history: Received Jul 24, 2018 Revised Nov 27, 2018 Accepted Dec 25, 2018 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. Keywords: Bhattacharyya distance k-NN Sliding algorithm Song recognition Copyright © 2019 Institute of Advanced Engineering and Science. All rights reserved. Corresponding Author: Dedy Rahman Wijaya, School of Applied Science, Telkom University, Jl. Telekomunikasi Terusan Buah Batu, Bandung 40257, Indonesia. Email: dedyrw@tass.telkomuniversity.ac.id 1. INTRODUCTION Music is a popular aspect of human life. Many people make music or listen to it while working, studying, or relaxing. In public places, songs are played to entertain visitors, who are often curious about what music they are listening to and want to know what song they are hearing. In addition, a music recognition system also can be used to detect illegally copied music. One problem that is difficult to handle is detection cover song. Cover songs are sung by different singers. Gender differences in singers, different sound colors, and improvised tones make it harder to detect. Several studies have been done in song recognition and several methods are applied in this field. In the previous studies, song recognition has been done by Multi-band Sum of Spectrogram, with 91% accuracy [1], and the PCA algorithm [2]. Cover song recognition has been done using the raw signal as input [3], [4]. From each of segment of the signal, the chroma will be obtained. This chroma can be used to recognize a cover song with 62% accuracy [5]-[7]. Other experiments used pitch [8]-[10], Information-Theoretic Measures of Similarity [11], music structure segmentation [12] and 2D Fourier Transform [13] to recognize cover songs. In a previous experiment, fingerprinting has been used to identify the title of a song based on the raw signal of the music. In another experiment, the fingerprint was gained and processed in spectrogram form. In our experiment, we used features from MPEG-7. The extraction of music features based on MPEG-7 in the form of a two-dimensional matrix, n x m. MPEG-7 has subband values for each feature. In a previous experiment, song recognition using fingerprinting was done by applying a sliding algorithm on a one-dimensional matrix [14]. This experiment kept the matrix obtained from MPEG-7 extraction. This activity is known as MIR. MIR means processing the music spectrogram to obtain useful information [15]. Song recognition (fingerprinting) and