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Improving the recognition of pathological voice using the discriminant HLDA transformation

Identifieur interne : 000903 ( Main/Exploration ); précédent : 000902; suivant : 000904

Improving 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 :

RBID : Hal:hal-01093309

English descriptors

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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Affiliations:


Links toward previous steps (curation, corpus...)


Le document en format XML

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