Publications de Rémi Gribonval

Blind Audio-Visual Source Separation based on Sparse Redundant Representations

Pierre Vandergheynst, Rémi Gribonval, Gianluca Monaci, Anna Llagostera Casanovas

In this paper we propose a novel method which is able to detect and separate audio-visual sources present in a scene. Our method exploits the correlation between the video signal captured with a camera and a synchronously recorded one-microphone audio trac ...

2010

Nonnegative Matrix Factorization and Spatial Covariance Model for Under-Determined Reverberant Audio Source Separation

Pierre Vandergheynst, Rémi Gribonval

We address the problem of blind audio source separation in the under-determined and convolutive case. The contribution of each source to the mixture channels in the time-frequency domain is modeled by a zero-mean Gaussian random vector with a full rank cov ...

2010

Double Sparsity: Towards Blind Estimation of Multiple Channels

Rémi Gribonval

We propose a framework for blind multiple filter estimation from convolutive mixtures, exploiting the time-domain sparsity of the mixing filters and the disjointness of the sources in the time-frequency domain. The proposed framework includes two steps: (a ...

Springer-Verlag's2010

A Robust Method to Count and Locate Audio Sources in a Multichannel Underdetermined Mixture

Rémi Gribonval

We propose a method to count and estimate the mixing directions in an underdetermined multichannel mixture. The approach is based on the hypothesis that in the neighbourhood of some time-frequency points, only one source essentially contributes to the mixt ...

Institute of Electrical and Electronics Engineers2010

Dictionary Identification - Sparse Matrix-Factorisation via $\ell_1$-Minimisation

Rémi Gribonval, Karin Schnass

This article treats the problem of learning a dictionary providing sparse representations for a given signal class, via

\ell_1

-minimisation. The problem can also be seen as factorising a

\ddim \times \nsig

matrix $Y=(y_1 \ldots y_\nsig), , y_n\in \R^\ ...

Institute of Electrical and Electronics Engineers2010

Compressive Sampling of Pulse Trains : Spread the Spectrum !

Pierre Vandergheynst, Rémi Gribonval, Laurent Jacques

In this paper we consider the problem of sampling far below the Nyquist rate signals that are sparse linear superpositions of shifts of a known, potentially wide-band, pulse. This signal model is key for applications such as Ultra Wide Band (UWB) communica ...

2009

A low complexity orthogonal matching pursuit for sparse signal approximation with shift-invariant dictionaries

Pierre Vandergheynst, Rémi Gribonval

We propose a variant of Orthogonal Matching Pursuit (OMP), called LoCOMP, for scalable sparse signal approximation. The algorithm is designed for shift- invariant signal dictionaries with localized atoms, such as time-frequency dictionaries, and achieves a ...

2009

Dictionary learning for the sparse modelling of atrial fibrillation in ECG signals

Pierre Vandergheynst, Jean-Marc Vesin, Rémi Gribonval

We propose a new method for ventricular cancellation and atrial modelling in the ECG of patients suffering from atrial fibrillation. Our method is based on dictionary learning. It extends both the average beat subtraction and the sparse source separation a ...

2009

Basis Identification from Random Sparse Samples

Rémi Gribonval, Karin Schnass

This article treats the problem of learning a dictionary providing sparse representations for a given signal class, via

\ell_1

minimisation. The problem is to identify a dictionary

\dico

from a set of training samples

\Y

knowing that

\Y = \dico \X

...

2009

Procédé et un dispositif d'estimation de signaux de source issus d'un signal de mélange

Rémi Gribonval

The invention pertains to the field of methods for estimating source signals from a multichannel mixture signal, and the aim of the invention is to carry out a reliable estimation of the properties of source signals without necessarily requiring prior info ...

2009

Rémi Gribonval

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Blind Audio-Visual Source Separation based on Sparse Redundant Representations

Nonnegative Matrix Factorization and Spatial Covariance Model for Under-Determined Reverberant Audio Source Separation

Double Sparsity: Towards Blind Estimation of Multiple Channels

A Robust Method to Count and Locate Audio Sources in a Multichannel Underdetermined Mixture

Dictionary Identification - Sparse Matrix-Factorisation via $\ell_1$-Minimisation

Compressive Sampling of Pulse Trains : Spread the Spectrum !

A low complexity orthogonal matching pursuit for sparse signal approximation with shift-invariant dictionaries

Dictionary learning for the sparse modelling of atrial fibrillation in ECG signals

Basis Identification from Random Sparse Samples

Procédé et un dispositif d'estimation de signaux de source issus d'un signal de mélange

Double Sparsity: Towards Blind Estimation of Multiple Channels

A low complexity orthogonal matching pursuit for sparse signal approximation with shift-invariant dictionaries

Basis Identification from Random Sparse Samples

Nonnegative Matrix Factorization and Spatial Covariance Model for Under-Determined Reverberant Audio Source Separation

A Robust Method to Count and Locate Audio Sources in a Multichannel Underdetermined Mixture

Dictionary Identification - Sparse Matrix-Factorisation via $\ell_1$-Minimisation

Dictionary learning for the sparse modelling of atrial fibrillation in ECG signals

Compressive Sampling of Pulse Trains : Spread the Spectrum !

Procédé et un dispositif d'estimation de signaux de source issus d'un signal de mélange

Blind Audio-Visual Source Separation based on Sparse Redundant Representations