Improving the recognition of pathological voice using the discriminant HLDA transformation
Identifieur interne : 002A37 ( Hal/Curation ); précédent : 002A36; suivant : 002A38Improving the recognition of pathological voice using the discriminant HLDA transformation
Auteurs : Othman Lachhab [France] ; Joseph Di Martino [France] ; El Hassane Ibn Elhaj [Maroc] ; Ahmed Hammouch [France]Source :
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Abstract
In this paper, we propose a simple and fast method for evaluating the pathological voice (esophageal) by applying the continuous speech recognition in a speaker dependent mode, on our own database of the pathological voice, we call FPSD (French Pathological Speech Database). The recognition system used is implemented using the HTK platform, based on HMM/GMM monophone models. The acoustic vectors are linearly transformed by the HLDA (Heteroscedastic Linear Discriminant Analysis) method to reduce their size in a smaller space with good discriminative properties. The obtained phone recognition rate (63.59 %) is very promising when we know that esophageal voice contains unnatural sounds, difficult to understand.
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<front><div type="abstract" xml:lang="en">In this paper, we propose a simple and fast method for evaluating the pathological voice (esophageal) by applying the continuous speech recognition in a speaker dependent mode, on our own database of the pathological voice, we call FPSD (French Pathological Speech Database). The recognition system used is implemented using the HTK platform, based on HMM/GMM monophone models. The acoustic vectors are linearly transformed by the HLDA (Heteroscedastic Linear Discriminant Analysis) method to reduce their size in a smaller space with good discriminative properties. The obtained phone recognition rate (63.59 %) is very promising when we know that esophageal voice contains unnatural sounds, difficult to understand.</div>
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<monogr><meeting><title>3rd International IEEE Colloquium on Information Science and Technology</title>
<date type="start">2014-10-20</date>
<date type="end">2014-10-22</date>
<settlement>Tetuan-Chefchaouen</settlement>
<country key="MA">Morocco</country>
</meeting>
<imprint><date type="datePub">2014</date>
</imprint>
</monogr>
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<profileDesc><langUsage><language ident="en">English</language>
</langUsage>
<textClass><keywords scheme="author"><term xml:lang="en">Automatic Speech Recognition (ASR)</term>
<term xml:lang="en">HMM</term>
<term xml:lang="en">HTK</term>
<term xml:lang="en">Pathological voices</term>
<term xml:lang="en">HLDA</term>
<term xml:lang="en">GMM</term>
<term xml:lang="en">MFCC</term>
</keywords>
<classCode scheme="halDomain" n="info.info-ts">Computer Science [cs]/Signal and Image Processing</classCode>
<classCode scheme="halTypology" n="COMM">Conference papers</classCode>
</textClass>
<abstract xml:lang="en">In this paper, we propose a simple and fast method for evaluating the pathological voice (esophageal) by applying the continuous speech recognition in a speaker dependent mode, on our own database of the pathological voice, we call FPSD (French Pathological Speech Database). The recognition system used is implemented using the HTK platform, based on HMM/GMM monophone models. The acoustic vectors are linearly transformed by the HLDA (Heteroscedastic Linear Discriminant Analysis) method to reduce their size in a smaller space with good discriminative properties. The obtained phone recognition rate (63.59 %) is very promising when we know that esophageal voice contains unnatural sounds, difficult to understand.</abstract>
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