Title
Multiple instrument mixtures source separation evaluation using instrument-dependent NMF models
Abstract
This work makes use of instrument-dependent models to separate the different sources of multiple instrument mixtures. Three different models are applied: (a) basic spectral model with harmonic constraint, (b) source-filter model with harmonic-comb excitation and (c) source-filter model with multi-excitation per instrument. The parameters of the models are optimized by an augmented NMF algorithm and learnt in a training stage. The models are presented in [1], here the experimental setting for the application to source separation is explained. The instrument-dependent NMF models are first trained and then a test stage is performed. A comparison with other state-of-the-art software is presented. Results show that source-filter model with multi-excitation per instrument outperforms the other compared models.
Year
DOI
Venue
2012
10.1007/978-3-642-28551-6_47
LVA/ICA
Keywords
Field
DocType
test stage,instrument-dependent model,separation evaluation,different model,different source,instrument-dependent nmf model,basic spectral model,source-filter model,multiple instrument mixtures source,augmented nmf algorithm,training stage,multiple instrument mixture
Pattern recognition,Computer science,Harmonic,Speech recognition,Software,Non-negative matrix factorization,Artificial intelligence,Spectral analysis,Source separation
Conference
Citations 
PageRank 
References 
3
0.41
8
Authors
5
Name
Order
Citations
PageRank
Francisco J. Rodriguez115319.73
Julio J. Carabias-Orti2906.34
Pedro Vera-Candeas39412.51
Virtanen Tuomas41883136.57
Nicolas Ruiz Reyes5112.30