Reconnaissance de la parole pour les locuteurs non natifs en présence de bruit
Identifieur interne : 003285 ( Crin/Corpus ); précédent : 003284; suivant : 003286Reconnaissance de la parole pour les locuteurs non natifs en présence de bruit
Auteurs : Dominique Fohr ; Odile Mella ; Irina Illina ; Fabrice Lauri ; Christophe Cerisara ; Christophe AntoineSource :
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Abstract
In real world applications, speech recognition is confronted with two main difficulties : the non native speakers and the background noise. The aim of this paper is to compare on the same noisy database different methods in order to increase the robustness of our HMM-based automatic speech recognition system. To deal with the non native speakers, we have tested two solutions : multi-models and adaptation techniques. For noisy speech, we have evaluated two types of methods : the first one (PMC and MLLR) adapts the initial models, trained in clean speech, with a few noisy sentences. The second one (RATZ and MCR) tries to remove the noise from the signal without modifying the HMM models.
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