Publications associées à A comparison of noise reduction techniques for robust speech recognition

A Virtual Simulation-Pilot Agent for Training of Air Traffic Controllers

Petr Motlicek, Juan Pablo Zuluaga Gomez, Amrutha Prasad

In this paper we propose a novel virtual simulation-pilot engine for speeding up air traffic controller (ATCo) training by integrating different state-of-the-art artificial intelligence (AI)-based tools. The virtual simulation-pilot engine receives spoken ...

MDPI2023

Supplementary datasets for the manuscript "Generative machine learning produces kinetic models that accurately characterize intracellular metabolic states" - Part 3

Vassily Hatzimanikatis, Ljubisa Miskovic, Michaël Roger Germain Moret

Supplementary files containing datasets needed to reproduce the results of the manuscript "Generative machine learning produces kinetic models that accurately characterize intracellular metabolic states" by S. Choudhury et al (https://doi.org/10.1101/2023. ...

EPFL Infoscience2023

A COMPARISON OF METHODS FOR OOV-WORD RECOGNITION ON A NEW PUBLIC DATASET

Petr Motlicek

A common problem for automatic speech recognition systems is how to recognize words that they did not see during training. Currently there is no established method of evaluating different techniques for tackling this problem. We propose using the CommonVoi ...

IEEE Signal Processing Society2021

Boosting of contextual information in ASR for air-traffic call-sign recognition

Petr Motlicek, Juan Pablo Zuluaga Gomez

Contextual adaptation of ASR can be very beneficial for multi-accent and often noisy Air-Traffic Control (ATC) speech. Our focus is call-sign recognition, which can be used to track conversations of ATC operators with individual airplanes. We developed a t ...

ISCA-INT SPEECH COMMUNICATION ASSOC2021

Objective evaluation of static beamforming on the quality of speech in noise

Hervé Lissek, Gilles André Courtois, Vincent Pierre Olivier Grimaldi

Beamforming is commonly used in devices such as in hearing instruments (HI) with a view to reducing noise. It consists in focusing on audio signals arising from a prescribed steering direction while suppressing those coming from other directions. The effic ...

European Acoustics Association2018

Agile text mining with Sherlok

Jean-Cédric Chappelier, Sean Lewis Hill, Renaud Luc Richardet

The successful development of an intelligent text mining application requires the collaboration of two main stakeholders: subject matter experts and text miners. In this paper, we describe a new methodology, agile text mining to improve that collaboration. ...

IEEE2015

Robust Log-Energy Estimation and its Dynamic Change Enhancement for In-car Speech Recognition

Hervé Bourlard, Weifeng Li

The log-energy parameter, typically derived from a full-band spectrum, is a critical feature commonly used in automatic speech recognition (ASR) systems. However, log-energy is difficult to estimate reliably in the presence of background noise. In this pap ...

Ieee-Inst Electrical Electronics Engineers Inc2013

Bias Adaptation for Vocal Tract Length Normalization

Philip Neil Garner, John David Scott Dines, Lakshmi Babu Saheer

Vocal tract length normalisation (VTLN) is a well known rapid adaptation technique. VTLN as a linear transformation in the cepstral domain results in the scaling and translation factors. The warping factor represents the spectral scaling parameter. While, ...

Idiap2013

Phase AutoCorrelation (PAC) features for noise robust speech recognition

Hynek Hermansky, Hemant Misra, Shajith Ikbal

In this paper, we introduce a new class of noise robust features derived from an alternative measure of autocorrelation representing the phase variation of speech signal frame over time. These features, referred to as Phase AutoCorrelation (PAC) features i ...

2012

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A comparison of noise reduction techniques for robust speech recognition

A Virtual Simulation-Pilot Agent for Training of Air Traffic Controllers

Supplementary datasets for the manuscript "Generative machine learning produces kinetic models that accurately characterize intracellular metabolic states" - Part 3

A COMPARISON OF METHODS FOR OOV-WORD RECOGNITION ON A NEW PUBLIC DATASET

Boosting of contextual information in ASR for air-traffic call-sign recognition

Objective evaluation of static beamforming on the quality of speech in noise

Combining the SNR Spectrum with a Cochlear Model

Agile text mining with Sherlok

Robust Log-Energy Estimation and its Dynamic Change Enhancement for In-car Speech Recognition

Bias Adaptation for Vocal Tract Length Normalization

Phase AutoCorrelation (PAC) features for noise robust speech recognition

Graph Chatbot

Chattez avec Graph Search

Agile text mining with Sherlok

A Virtual Simulation-Pilot Agent for Training of Air Traffic Controllers

Supplementary datasets for the manuscript "Generative machine learning produces kinetic models that accurately characterize intracellular metabolic states" - Part 3

Combining the SNR Spectrum with a Cochlear Model

Objective evaluation of static beamforming on the quality of speech in noise

Boosting of contextual information in ASR for air-traffic call-sign recognition

Robust Log-Energy Estimation and its Dynamic Change Enhancement for In-car Speech Recognition

A COMPARISON OF METHODS FOR OOV-WORD RECOGNITION ON A NEW PUBLIC DATASET

Bias Adaptation for Vocal Tract Length Normalization

Phase AutoCorrelation (PAC) features for noise robust speech recognition