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Hilbert Envelope Based Features for Far-Field Speech Recognition

Publications associées (48)

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Development of Bilingual ASR System for MediaParl Corpus

Petr Motlicek, Milos Cernak, David Imseng

The development of an Automatic Speech Recognition (ASR) system for the bilingual MediaParl corpus is challenging for several reasons: (1) reverberant recordings, (2) accented speech, and (3) no prior information about the language. In that context, we emp ...

Idiap2014

A Savitzky-Golay Filtering Perspective of Dynamic Feature Computation

Mathew Magimai Doss, Chandra Sekhar Seelamantula

We address the classical problem of delta feature computation, and interpret the operation involved in terms of Savitzky-Golay (SG) filtering. Features such as the mel-frequency cepstral coefficients (MFCCs), obtained based on short-time spectra of the spe ...

2013

Privacy-Sensitive Audio Features for Speech/Nonspeech Detection

Hervé Bourlard, Daniel Gatica-Perez, Sree Hari Krishnan Parthasarathi

The goal of this paper is to investigate features for speech/nonspeech detection (SND) having ``minimal'' linguistic information from the speech signal. Towards this, we present a comprehensive study of privacy-sensitive features for SND in multiparty conv ...

Idiap2011

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

We present a proposal of a kernel-based model for large vocabulary continuous speech recognizer. The continuous speech recognition is described as a problem of finding the best phoneme sequence and its best time span, where the phonemes are generated from ...

John Wiley and Sons2009

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

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

Hynek Hermansky, Sriram Ganapathy, Samuel Thomas

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

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IDIAP2008

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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

IDIAP2008