Title | ||
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Multiple instrument mixtures source separation evaluation using instrument-dependent NMF models |
Abstract | ||
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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 |
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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. Rodriguez | 1 | 153 | 19.73 |
Julio J. Carabias-Orti | 2 | 90 | 6.34 |
Pedro Vera-Candeas | 3 | 94 | 12.51 |
Virtanen Tuomas | 4 | 1883 | 136.57 |
Nicolas Ruiz Reyes | 5 | 11 | 2.30 |