Publications related to Front-end for Far-field Speech Recognition based on Frequency Domain Linear Prediction

ROXANNE Research Platform: Automate criminal investigations

Petr Motlicek, Maël Fabien, Aravind Krishnan

Criminal investigations require manual intervention of several investigators and translators. However, the amount and the diversity of the data collected raises many challenges, and cross-border investigations against organized crime can quickly impossible ...

ISCA-INT SPEECH COMMUNICATION ASSOC2021

Detecting Trends in Job Advertisements

Pierre Dillenbourg, Kshitij Sharma, Khalil Mrini

We present an automatic method for trend detection in job ads. From a job-posting website, we collect job ads from 16 countries and in 8 languages and 6 job domains. We pre-process them by removing stop words, lemmatising and performing cross-domain filter ...

2017

Supervised and unsupervised Web-based language model domain adaptation

Petr Motlicek, John David Scott Dines

Domain language model adaptation consists in re-estimating probabilities of a baseline LM in order to better match the specifics of a given broad topic of interest. To do so, a common strategy is to retrieve adaptation texts from the Web based on a given d ...

2012

Supervised and unsupervised Web-based language model domain adaptation

Petr Motlicek, John David Scott Dines

Domain language model adaptation consists in re-estimating probabilities of a baseline LM in order to better match the specifics of a given broad topic of interest. To do so, a common strategy is to retrieve adaptation texts from the Web based on a given d ...

Idiap2012

Beamforming with a Maximum Negentropy Criterion

Philip Neil Garner, Weifeng Li

In this paper, we address a beamforming application based on the capture of far-field speech data from a single speaker in a real meeting room. After the position of the speaker is estimated by a speaker tracking system, we construct a subband-domain beamf ...

2009

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Automatic Speech Recognition (ASR) systems usually fail when they encounter speech from far-field microphone in reverberant environments. This is due to the application of short-term feature extraction techniques which do not compensate for the artifacts i ...

2008

Recognition Of Reverberant Speech Using Frequency Domain Linear Prediction

Hynek Hermansky, Sriram Ganapathy, Samuel Thomas

Performance of a typical automatic speech recognition (ASR) system severely degrades when it encounters speech from reverberant environments. Part of the reason for this degradation is the feature extraction techniques that use analysis windows which are m ...

2008

Recognition Of Reverberant Speech Using Frequency Domain Linear Prediction

Hynek Hermansky, Sriram Ganapathy, Samuel Thomas

Performance of a typical automatic speech recognition (ASR) system severely degrades when it encounters speech from reverberant environments. Part of the reason for this degradation is the feature extraction techniques that use analysis windows which are m ...

IDIAP2008

Hilbert Envelope Based Features for Far-Field Speech Recognition

Hynek Hermansky, Sriram Ganapathy, Samuel Thomas

Automatic speech recognition (ASR) systems, trained on speech signals from close-talking microphones, generally fail in recognizing far-field speech. In this paper, we present a Hilbert Envelope based feature extraction technique to alleviate the artifacts ...

2008

Hilbert Envelope Based Features for Far-Field Speech Recognition

Hynek Hermansky, Sriram Ganapathy, Samuel Thomas

Automatic speech recognition (ASR) systems, trained on speech signals from close-talking microphones, generally fail in recognizing far-field speech. In this paper, we present a Hilbert Envelope based feature extraction technique to alleviate the artifacts ...

IDIAP2008

Front-end for Far-field Speech Recognition based on Frequency Domain Linear Prediction

ROXANNE Research Platform: Automate criminal investigations

Detecting Trends in Job Advertisements

Supervised and unsupervised Web-based language model domain adaptation

Supervised and unsupervised Web-based language model domain adaptation

Beamforming with a Maximum Negentropy Criterion

Recognition Of Reverberant Speech Using Frequency Domain Linear Prediction

Recognition Of Reverberant Speech Using Frequency Domain Linear Prediction

Hilbert Envelope Based Features for Far-Field Speech Recognition

Hilbert Envelope Based Features for Far-Field Speech Recognition

Graph Chatbot

Chat with Graph Search

Supervised and unsupervised Web-based language model domain adaptation

Supervised and unsupervised Web-based language model domain adaptation

Detecting Trends in Job Advertisements

Hilbert Envelope Based Features for Far-Field Speech Recognition

Hilbert Envelope Based Features for Far-Field Speech Recognition

Recognition Of Reverberant Speech Using Frequency Domain Linear Prediction

Recognition Of Reverberant Speech Using Frequency Domain Linear Prediction

ROXANNE Research Platform: Automate criminal investigations

Beamforming with a Maximum Negentropy Criterion