DocumentCode :
1653386
Title :
Efficient database pruning for large-scale cover song recognition
Author :
Osmalskyj, J. ; Pierard, S. ; Van Droogenbroeck, M. ; Embrechts, J.J.
Author_Institution :
Dept. EECS, Univ. of Liege, Liege, Belgium
fYear :
2013
Firstpage :
714
Lastpage :
718
Abstract :
This paper focuses on cover song recognition over a large dataset, potentially containing millions of songs. At this time, the problem of cover song recognition is still challenging and only few methods have been proposed on large scale databases. We present an efficient method for quickly extracting a small subset from a large database in which a correspondence to an audio query should be found. We make use of fast rejectors based on independent audio features. Our method mixes independent rejectors together to build composite ones. We evaluate our system with the Million Song Dataset and we present composite rejectors offering a good trade-off between the percentage of pruning and the percentage of loss.
Keywords :
audio signal processing; music; query processing; Million Song dataset; audio query; composite rejectors; cover song recognition; database pruning; independent audio features; music information retrieval; Abstracts; Databases; Chromas; Cover Songs; Million Song Dataset; Music Information Retrieval; Rejectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on
Conference_Location :
Vancouver, BC
ISSN :
1520-6149
Type :
conf
DOI :
10.1109/ICASSP.2013.6637741
Filename :
6637741
Link To Document :
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