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Published in:
2012 | OriginalPaper | Chapter
Multiple Instrument Mixtures Source Separation Evaluation Using Instrument-Dependent NMF Models
Authors : Francisco J. Rodriguez-Serrano, Julio J. Carabias-Orti, Pedro Vera-Candeas, Tuomas Virtanen, Nicolas Ruiz-Reyes
Published in: Latent Variable Analysis and Signal Separation
Publisher: Springer Berlin Heidelberg
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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.