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IMPROVING MICROPHONE ARRAY SPEECH RECOGNITION WITH COCHLEAR IMPLANT-LIKE SPECTRALLY REDUCED SPEECH

Publications associées (33)

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Hitting with Probability One for Stochastic Heat Equations with Additive Noise

Robert Dalang, Fei Pu

We study the hitting probabilities of the solution to a system of d stochastic heat equations with additive noise subject to Dirichlet boundary conditions. We show that for any bounded Borel set with positive (d-6)\documentclass[12pt]{minimal} \usepackage{ ...

Springer/Plenum Publishers2024

The Almost-Sure Asymptotic Behavior Of The Solution To The Stochastic Heat Equation With Levy Noise

Carsten Hao Ye Chong

We examine the almost-sure asymptotics of the solution to the stochastic heat equation driven by a Levy space-time white noise. When a spatial point is fixed and time tends to infinity, we show that the solution develops unusually high peaks over short tim ...

INST MATHEMATICAL STATISTICS2020

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We propose a novel algorithm to design an optimum array geometry for source localization inside an enclosure. We assume a square-law decay propagation model for the sound acquisition so that the additive noise on the measured source-microphone distances is ...

2015

The Poisson likelihood with rectified linear function as non-linearity is a physically plausible model to discribe the stochastic arrival process of photons or other particles at a detector. At low emission rates the discrete nature of this process leads t ...

2015

A Projected Gradient Algorithm for Image Restoration Under Hessian Matrix-Norm Regularization

Michaël Unser, Stamatios Lefkimmiatis

We have recently introduced a class of non-quadratic Hessian-based regularizers as a higher-order extension of the total variation (TV) functional. These regularizers retain some of the most favorable properties of TV while they can effectively deal with t ...

IEEE2012

Cepstral normalisation and the signal to noise ratio spectrum in automatic speech recognition.

Philip Neil Garner

Cepstral normalisation in automatic speech recognition is investigated in the context of robustness to additive noise. It is argued that such normalisation leads naturally to a speech feature based on signal to noise ratio rather than absolute energy (or p ...

Idiap2011

Cepstral normalisation and the signal to noise ratio spectrum in automatic speech recognition

Philip Neil Garner

Cepstral normalisation in automatic speech recognition is investigated in the context of robustness to additive noise. In this paper, it is argued that such normalisation leads naturally to a speech feature based on signal to noise ratio rather than absolu ...

2011

This paper demonstrates the robustness of group delay based features to additive noise. First, we analytically show the robustness of group delay based represen- tations. The analysis makes use of the fact that, for minimum-phase signals, the group delay f ...

2011

BOOSTED BINARY FEATURES FOR NOISE-ROBUST SPEAKER VERIFICATION

Sébastien Marcel, Anindya Roy

The standard approach to speaker verification is to extract cepstral features from the speech spectrum and model them by generative or discriminative techniques. We propose a novel approach where a set of client-specific binary features carrying maximal di ...

2010

Visual processing-inspired Fern-Audio features for Noise-Robust Speaker Verification

Sébastien Marcel, Anindya Roy

In this paper, we consider the problem of speaker verification as a two-class object detection problem in computer vision, where the object instances are 1-D short-time spectral vectors obtained from the speech signal. More precisely, we investigate the ge ...

2010