Music Information Retrieval; Audio classifiers; Similarity; Low-level audio features; Rejectors
Abstract :
[en] This paper proposes a survey of the performances of binary classifiers based on low-level audio features, for music similarity in large-scale databases. Various low-level descriptors are used individually and then combined using several fusion schemes in a content-based audio retrieval system. We show the performances of the classifiers in terms of pruning and loss and we demonstrate that some combination schemes achieve a better performance at a minimum computational cost.
Research center :
INTELSIG
Disciplines :
Computer science
Author, co-author :
Osmalsky, Julien ; Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Techniques du son et de l'image
Van Droogenbroeck, Marc ; Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Télécommunications
Embrechts, Jean-Jacques ; Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Techniques du son et de l'image
Language :
English
Title :
Performances of low-level audio classifiers for large-scale music similarity
Publication date :
May 2014
Event name :
International Conference on Systems, Signals and Image Processing (IWSSIP)
Event place :
Dubrovnik, Croatia
Event date :
from 12-05-2014 to 15-05-2014
Audience :
International
Main work title :
International Conference on Systems, Signals and Image Processing