Publications related to Multi-party Speech Recovery Exploiting Structured Sparsity Models

Binary Sparse Coding of Convolutive Mixtures for Sound Localization and Separation via Spatialization

Hervé Bourlard, Volkan Cevher, Afsaneh Asaei, Mohammadjavad Taghizadeh, Saeid Haghighatshoar

We propose a sparse coding approach to address the problem of source-sensor localization and speech reconstruction. This approach relies on designing a dictionary of spatialized signals by projecting the microphone array recordings into the array manifolds ...

Institute of Electrical and Electronics Engineers2016

‪Stochastic Control-A Moment Approach to Sparse Control Design‬

We consider design of sparse controllers for a stochastic linear system with infinite horizon quadratic objective. We formulate the non-sparse optimal solution through a semidefinite program for the second order moments of the states and inputs. Given that ...

University of Minnesota2016

Estimation Error of the Constrained Lasso

Volkan Cevher, Yen-Huan Li, Ya-Ping Hsieh, Nissim Zerbib

This paper presents a non-asymptotic upper bound for the estimation error of the constrained lasso, under the high-dimensional (

n \ll p

) setting. In contrast to existing results, the error bound in this paper is sharp, is valid when the parameter to be e ...

2016

Signal structure: from manifolds to molecules and structured sparsity

Sofia Karygianni

Effective representation methods and proper signal priors are crucial in most signal processing applications. In this thesis we focus on different structured models and we design appropriate schemes that allow the discovery of low dimensional latent struct ...

EPFL2015

On Compressibility of Neural Network phonological Features for Low Bit Rate Speech Coding

Hervé Bourlard, Milos Cernak, Afsaneh Asaei

Phonological features extracted by neural network have shown interesting potential for low bit rate speech vocoding. The span of phonological features is wider than the span of phonetic features, and thus fewer frames need to be transmitted. Moreover, the ...

2015

Structured Sparsity Models for Reverberant Speech Separation

Hervé Bourlard, Volkan Cevher, Afsaneh Asaei, Mohammad Golbabaee

We tackle the multi-party speech recovery problem through modeling the acoustic of the reverberant chambers. Our approach exploits structured sparsity models to perform room modeling and speech recovery. We propose a scheme for characterizing the room acou ...

2014

Jump-Sparse and Sparse Recovery Using Potts Functionals

Martin Kurt Storath

We recover jump-sparse and sparse signals from blurred incomplete data corrupted by (possibly non-Gaussian) noise using inverse Potts energy functionals. We obtain analytical results (existence of minimizers, complexity) on inverse Potts functionals and pr ...

Ieee-Inst Electrical Electronics Engineers Inc2014

Sparse Gammatone Signal Model Predicts Perceived Noise Intrusiveness

Hervé Bourlard, Raphaël Marc Ullmann

Is it possible to predict the intrusiveness of background noise in speech signals as perceived by humans? Such a question is important to the automatic evaluation of speech enhancement systems, including those designed for new wideband speech telephony, an ...

Idiap2014

A geometric framework for registration of sparse images

Pascal Frossard, Alhussein Fawzi

We examine the problem of image registration when images have a sparse representation in a dictionary of geometric features. We propose a novel algorithm for aligning images by pairing their sparse components. We show numerically that this algorithm works ...

2013

Image registration with sparse approximations in parametric dictionaries

Pascal Frossard, Alhussein Fawzi

We examine in this paper the problem of image registration from the new perspective where images are given by sparse approximations in parametric dictionaries of geometric functions. We propose a registration algorithm that looks for an estimate of the glo ...

2013

Multi-party Speech Recovery Exploiting Structured Sparsity Models

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Binary Sparse Coding of Convolutive Mixtures for Sound Localization and Separation via Spatialization

‪Stochastic Control-A Moment Approach to Sparse Control Design‬

Estimation Error of the Constrained Lasso

Signal structure: from manifolds to molecules and structured sparsity

On Compressibility of Neural Network phonological Features for Low Bit Rate Speech Coding

Structured Sparsity Models for Reverberant Speech Separation

Jump-Sparse and Sparse Recovery Using Potts Functionals

Sparse Gammatone Signal Model Predicts Perceived Noise Intrusiveness

A geometric framework for registration of sparse images

Image registration with sparse approximations in parametric dictionaries

Estimation Error of the Constrained Lasso

Binary Sparse Coding of Convolutive Mixtures for Sound Localization and Separation via Spatialization

Signal structure: from manifolds to molecules and structured sparsity

‪Stochastic Control-A Moment Approach to Sparse Control Design‬

On Compressibility of Neural Network phonological Features for Low Bit Rate Speech Coding

Structured Sparsity Models for Reverberant Speech Separation

Jump-Sparse and Sparse Recovery Using Potts Functionals

Image registration with sparse approximations in parametric dictionaries

Sparse Gammatone Signal Model Predicts Perceived Noise Intrusiveness

A geometric framework for registration of sparse images