An experimental evaluation of Wiener filter smoothing techniques applied to under-determined audio source separation

Emmanuel Vincent 1
1 METISS - Speech and sound data modeling and processing
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
Abstract : Multichannel under-determined source separation is often carried out in the time-frequency domain by estimating the source coefficients in each time-frequency bin based on some sparsity assumption. Due to the limited amount of data, this estimation is often inaccurate and results in musical noise artifacts. A number of single- and multichannel smoothing techniques have been introduced to reduce such artifacts in the context of speech denoising but have not yet been systematically applied to under-determined source separation. We present some of these techniques, extend them to multichannel input when needed, and compare them on a set of speech and music mixtures. Many techniques initially designed for diffuse and/or stationary interference appear to fail with directional nonstationary interference. Temporal covariance smoothing provides the best tradeoff between artifacts and interference and increases the overall signal-to-distortion ratio by up to 3 dB.
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Emmanuel Vincent. An experimental evaluation of Wiener filter smoothing techniques applied to under-determined audio source separation. 9th Int. Conf. on Latent Variable Analysis and Signal Separation (LVA/ICA), Sep 2010, Saint-Malo, France. pp.157--164. ⟨inria-00544035⟩

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