Title
Improving PLCA-based score-informed source separation with invertible constant-Q transforms Improving PLCA-based score-informed source separation with invertible constant-Q transforms
Author
Faculty/Department
Faculty of Sciences. Physics
Publication type
bookPart
Publication
S.l. , [*]
Subject
Physics
Source (book)
EUSIPCO 2012, 20th European Signal Processing Conference, Bucharest, Romania, August 27-31
ISSN
2076-1465
ISBN - Hoofdstuk
978-1-4673-1068-0
ISI
000310623800530
Carrier
E
Target language
English (eng)
Affiliation
University of Antwerp
Abstract
Probabilistic Latent Component Analysis is a widely adopted variant of Nonnegative Matrix Factorization for the purpose of single channel audio source separation. It has seen many extensions, including incorporation of prior information derived from music scores. Recent work on the invertibility of the Constant-Q Tranform make that a viable alternative to the Short-time Fourier Transform as underlying data representation. In this paper we assess several implementations for their usability in score-informed source separation. We show that results are comparable to, and in some cases better than, use of the STFT, and that exact transform invertibility is not a significant factor in this application.
E-info
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000310623800530&DestLinkType=RelatedRecords&DestApp=ALL_WOS&UsrCustomerID=ef845e08c439e550330acc77c7d2d848
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000310623800530&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=ef845e08c439e550330acc77c7d2d848
Handle