Title :
Music fingerprint extraction for classical music cover song identification
Author :
Kim, Samuel ; Unal, Erdem ; Narayanan, Shrikanth
Author_Institution :
Speech Anal. & Interpretation Lab. (SAIL), Southern California Univ., Los Angeles, CA
fDate :
June 23 2008-April 26 2008
Abstract :
An algorithm for extracting music fingerprints directly from an audio signal is proposed in this paper. The proposed music fingerprint aims to encapsulate various aspects of musical information, such as overall note distribution, harmony structure, and their temporal changes, all in a compact representation. The utility of the proposed music fingerprint to the task of automatic classical music cover song identification is explored through experimental studies; specifically, the goal here is to identify the different versions of the same music through similarity comparisons of the music fingerprints. The results show an improved performance over the state-of-the-art cover song identification systems in terms of both accuracy and speed: the accuracy improved by approximately 40% while the search speed is about 60 times faster than the conventional system.
Keywords :
information retrieval; music; automatic classical music; classical music cover song identification; music fingerprint extraction; musical information; Data mining; Fingerprint recognition; Hidden Markov models; Instruments; Libraries; Mel frequency cepstral coefficient; Multiple signal classification; Music information retrieval; Signal processing; Speech analysis;
Conference_Titel :
Multimedia and Expo, 2008 IEEE International Conference on
Conference_Location :
Hannover
Print_ISBN :
978-1-4244-2570-9
Electronic_ISBN :
978-1-4244-2571-6
DOI :
10.1109/ICME.2008.4607671