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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)

- David K. Hammond, Pierre Vandergheynst, Rémi Gribonval
- ArXiv
- 2009

We propose a novel method for constructing wavelet transforms of functions defined on the vertices of an arbitrary finite weighted graph. Our approach is based on defining scaling using the graph analogue of the Fourier domain, namely the spectral decomposition of the discrete graph Laplacian L. Given a wavelet generating kernel g and a scale parameter t,… (More)

- Rémi Gribonval, Morten Nielsen
- IEEE Trans. Information Theory
- 2003

The purpose of this correspondence is to generalize a result by Donoho and Huo and Elad and Bruckstein on sparse representations of signals in a union of two orthonormal bases for . We consider general (redundant) dictionaries for , and derive sufficient conditions for having uniquesparserepresentations of signals insuchdictionaries.Thespecial case where… (More)

- Ngoc Q. K. Duong, Emmanuel Vincent, Rémi Gribonval
- IEEE Transactions on Audio, Speech, and Language…
- 2010

This paper addresses the modeling of reverberant recording environments in the context of under-determined convolutive blind source separation. We model the contribution of each source to all mixture channels in the time-frequency domain as a zero-mean Gaussian random variable whose covariance encodes the spatial characteristics of the source. We then… (More)

- Sangnam Nam, Mike E. Davies, Michael Elad, Rémi Gribonval
- ArXiv
- 2011

After a decade of extensive study of the sparse representation synthesis model, we can safely say that this is a mature and stable field, with clear theoretical foundations, and appealing applications. Alongside this approach, there is an analysis counterpart model, which, despite its similarity to the synthesis alternative, is markedly different.… (More)

- Rémi Gribonval, Sylvain Lesage
- ESANN
- 2006

This paper provides new results on computing simultaneous sparse approximations of multichannel signals over redundant dictionaries using two greedy algorithms. The first one, p-thresholding, selects the S atoms that have the largest p-correlation while the second one, p-simultaneous matching pursuit (p-SOMP), is a generalisation of an algorithm studied by… (More)

- Sylvain Lesage, Rémi Gribonval, Frédéric Bimbot, Laurent Benaroya
- ICASSP
- 2005

We propose a new method to learn overcomplete dictionaries for sparse coding structured as unions of orthonormal bases. The interest of such a structure is manifold. Indeed, it seems that many signals or images can be modeled as the superimposition of several layers with sparse decompositions in as many bases. Moreover, in such dictionaries, the efficient… (More)

- Laurent Benaroya, Frédéric Bimbot, Rémi Gribonval
- IEEE Transactions on Audio, Speech, and Language…
- 2006

In this paper, we address the problem of audio source separation with one single sensor, using a statistical model of the sources. The approach is based on a learning step from samples of each source separately, during which we train Gaussian scaled mixture models (GSMM). During the separation step, we derive maximum a posteriori (MAP) and/or posterior mean… (More)

- Rémi Gribonval, Pierre Vandergheynst
- IEEE Transactions on Information Theory
- 2006

The purpose of this correspondence is to extend results by Villemoes and Temlyakov about exponential convergence of Matching Pursuit (MP) with some structured dictionaries for "simple" functions in finite or infinite dimension. The results are based on an extension of Tropp's results about Orthogonal Matching Pursuit (OMP) in finite dimension, with the… (More)