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Reconnaissance de la parole pour les locuteurs non natifs en présence de bruit

Dominique Fohr 1 Odile Mella 1 Irina Illina 1 Fabrice Lauri 1 Christophe Cerisara 1 Christophe Antoine 1
1 PAROLE - Analysis, perception and recognition of speech
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
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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Submitted on : Tuesday, September 26, 2006 - 2:50:59 PM
Last modification on : Friday, February 26, 2021 - 3:28:05 PM


  • HAL Id : inria-00100780, version 1



Dominique Fohr, Odile Mella, Irina Illina, Fabrice Lauri, Christophe Cerisara, et al.. Reconnaissance de la parole pour les locuteurs non natifs en présence de bruit. XXIVèmes Journées d'Etude sur la Parole - JEP'02, Jun 2002, Nancy, France, pp.297-301. ⟨inria-00100780⟩



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