TY - GEN
T1 - Cover song recognition based on MPEG-7 audio features
AU - Ponighzwa, R. Mochammad Faris
AU - Sarno, Riyanarto
AU - Sunaryono, Dwi
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/1
Y1 - 2017/7/1
N2 - Lately, song industry has developed rapidly throughout the world. In the past, there were many applications which used song as their main themes, such as Shazam and Sound hound. Shazam and Sound hound could identify a song based on recorded one through the application. These applications work by matching the recorded song with an original song in the database. However, matching process is only based on the particular part of the spectrogram instead of an entire song's spectrogram. The disadvantages of this method arise though. This application could only identify the recorded original song. When application recorded a cover song, it cannot identify the title of the original song's since the spectrogram of a cover performance's and its original song's is entirely different. This paper exists to discuss how to recognize a cover song based on MPEG-7 standard ISO. KNN was used as classification method and combined with Audio Spectrum Projection and Audio Spectrum Flatness feature from MPEG-7 extraction. The result from this method identifies an original song from recorded cover of the original one. Result for experiment in this paper is about 75-80%, depends on testing data; whether the testing data is a dominant vocal song or dominant instrument song.
AB - Lately, song industry has developed rapidly throughout the world. In the past, there were many applications which used song as their main themes, such as Shazam and Sound hound. Shazam and Sound hound could identify a song based on recorded one through the application. These applications work by matching the recorded song with an original song in the database. However, matching process is only based on the particular part of the spectrogram instead of an entire song's spectrogram. The disadvantages of this method arise though. This application could only identify the recorded original song. When application recorded a cover song, it cannot identify the title of the original song's since the spectrogram of a cover performance's and its original song's is entirely different. This paper exists to discuss how to recognize a cover song based on MPEG-7 standard ISO. KNN was used as classification method and combined with Audio Spectrum Projection and Audio Spectrum Flatness feature from MPEG-7 extraction. The result from this method identifies an original song from recorded cover of the original one. Result for experiment in this paper is about 75-80%, depends on testing data; whether the testing data is a dominant vocal song or dominant instrument song.
KW - KNN
KW - MPEG-7
KW - cover song recognition
UR - http://www.scopus.com/inward/record.url?scp=85046680088&partnerID=8YFLogxK
U2 - 10.1109/ICSITech.2017.8257086
DO - 10.1109/ICSITech.2017.8257086
M3 - Conference contribution
AN - SCOPUS:85046680088
T3 - Proceeding - 2017 3rd International Conference on Science in Information Technology: Theory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017
SP - 59
EP - 65
BT - Proceeding - 2017 3rd International Conference on Science in Information Technology
A2 - Riza, Lala Septem
A2 - Pranolo, Andri
A2 - Wibawa, Aji Prasetyo
A2 - Junaeti, Enjun
A2 - Wihardi, Yaya
A2 - Hashim, Ummi Raba'ah
A2 - Horng, Shi-Jinn
A2 - Drezewski, Rafal
A2 - Lim, Heui Seok
A2 - Chakraborty, Goutam
A2 - Hernandez, Leonel
A2 - Nazir, Shah
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 3rd International Conference on Science in Information Technology, ICSITech 2017
Y2 - 25 October 2017 through 26 October 2017
ER -