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- Emmanuel Vincent, Rémi Gribonval, Cédric Févotte
- IEEE Transactions on Audio, Speech, and Language…
- 2006

In this paper, we discuss the evaluation of blind audio source separation (BASS) algorithms. Depending on the exact application, different distortions can be allowed between an estimated source and the wanted true source. We consider four different sets of such allowed distortions, from time-invariant gains to time-varying filters. In each case, we… (More)

- Cédric Févotte, Jérôme Idier
- Neural Computation
- 2011

This letter describes algorithms for nonnegative matrix factorization (NMF) with the β-divergence (β-NMF). The β-divergence is a family of cost functions parameterized by a single shape parameter β that takes the Euclidean distance, the Kullback-Leibler divergence, and the Itakura-Saito divergence as special cases (β = 2, 1, 0 respectively). The proposed… (More)

- Cédric Févotte, Nancy Bertin, Jean-Louis Durrieu
- Neural Computation
- 2009

This letter presents theoretical, algorithmic, and experimental results about nonnegative matrix factorization (NMF) with the Itakura-Saito (IS) divergence. We describe how IS-NMF is underlaid by a well-defined statistical model of superimposed gaussian components and is equivalent to maximum likelihood estimation of variance parameters. This setting can… (More)

- Alexey Ozerov, Cédric Févotte
- IEEE Transactions on Audio, Speech, and Language…
- 2010

We consider inference in a general data-driven object-based model of multichannel audio data, assumed generated as a possibly underdetermined convolutive mixture of source signals. We work in the short-time Fourier transform (STFT) domain, where convolution is routinely approximated as linear instantaneous mixing in each frequency band. Each source STFT is… (More)

- Jean-Louis Durrieu, Gaël Richard, Bertrand David, Cédric Févotte
- IEEE Transactions on Audio, Speech, and Language…
- 2010

Extracting the main melody from a polyphonic music recording seems natural even to untrained human listeners. To a certain extent it is related to the concept of source separation, with the human ability of focusing on a specific source in order to extract relevant information. In this paper, we propose a new approach for the estimation and extraction of… (More)

- Cédric Févotte, Jérôme Idier
- ArXiv
- 2010

This paper describes algorithms for nonnegative matrix factorization (NMF) with the β-divergence (β-NMF). The β-divergence is a family of cost functions parametrized by a single shape parameter β that takes the Euclidean distance, the Kullback-Leibler divergence and the Itakura-Saito divergence as special cases (β = 2, 1, 0 respectively). The proposed… (More)

- Vincent Y. F. Tan, Cédric Févotte
- IEEE Trans. Pattern Anal. Mach. Intell.
- 2013

This paper addresses the estimation of the latent dimensionality in nonnegative matrix factorization (NMF) with the β-divergence. The β-divergence is a family of cost functions that includes the squared euclidean distance, Kullback-Leibler (KL) and Itakura-Saito (IS) divergences as special cases. Learning the model order is important as it is necessary to… (More)

- Cédric Févotte, Simon J. Godsill
- IEEE Transactions on Audio, Speech, and Language…
- 2006

We present a Bayesian approach for blind separation of linear instantaneous mixtures of sources having a sparse representation in a given basis. The distributions of the coefficients of the sources in the basis are modeled by a Student t distribution, which can be expressed as a scale mixture of Gaussians, and a Gibbs sampler is derived to estimate the… (More)

In this paper, we address a few issues related to the evaluation of the performance of source separation algorithms. We propose several measures of distortion that take into account the gain indeterminacies of BSS algorithms. The total distortion includes interference from the other sources as well as noise and algorithmic artifacts, and we define… (More)

- Cédric Févotte, Christian Doncarli
- IEEE Signal Processing Letters
- 2004

We present two improvements/extensions of a previous deterministic blind source separation (BSS) technique, by Belouchrani and Amin, that involves joint-diagonalization of a set of Cohen's class spatial time-frequency distributions. The first contribution concerns the extension of the BSS technique to the stochastic case using spatial Wigner-Ville spectrum.… (More)