On the Use of Latent Mixing Filters in Audio Source Separation

Laurent Girin 1, 2 Roland Badeau 3, 4
1 PERCEPTION - Interpretation and Modelling of Images and Videos
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble
2 GIPSA-CRISSP - CRISSP
GIPSA-DPC - Département Parole et Cognition
Abstract : In this paper, we consider the underdetermined convolutive audio source separation (UCASS) problem. In the STFT domain, we consider both source signals and mixing filters as latent random variables, and we propose to estimate each source image, i.e. each individual source-filter product, by its posterior mean. Although, this is a quite straightforward application of the Bayesian estimation theory, to our knowledge, there exist no similar study in the UCASS context. In this paper, we discuss the interest of this estimator in this context and com- pare it with the conventional Wiener filter in a semi-oracle configuration.
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https://hal.archives-ouvertes.fr/hal-01400965
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Submitted on : Monday, March 20, 2017 - 6:00:14 PM
Last modification on : Thursday, October 17, 2019 - 12:36:10 PM

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Laurent Girin, Roland Badeau. On the Use of Latent Mixing Filters in Audio Source Separation. 13th International Conference on Latent Variable Analysis and Signal Separation (LVA/ICA 2017), Feb 2017, Grenoble, France. pp.225-235, ⟨10.1007/978-3-319-53547-0_22⟩. ⟨hal-01400965⟩

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