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
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;
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on
Conference_Location :
Vancouver, BC
DOI :
10.1109/ICASSP.2013.6637741