Statistical pronunciation modeling for non-native speech processing

In this work, the authors present a fully statistical approach to model non--native speakers' pronunciation. Second-language speakers pronounce words in multiple different ways compared to the native speakers. Those deviations, may it be phoneme substitutions, deletions or insertions, can be mo...

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Détails bibliographiques
Auteurs principaux: Gruhn, Rainer E., 19..-, Minker, Wolfgang, 1967- (Auteur), Nakamura, Satoshi, 19..- (Auteur)
Format: Livre numérique
Langue:Anglais
Publié: Berlin, Heidelberg : Springer Berlin Heidelberg 2011.
Cham : Springer Nature
Collection:Signals and Communication Technology
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Note: Archives Springer e-books (Licence nationale)
Archives Springer e-books (Licence nationale)
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Edition sous un autre format:• Statistical Pronunciation Modeling for Non-Native Speech Processing, Texte imprimé, 9783642195853
• Statistical Pronunciation Modeling for Non-Native Speech Processing, Texte imprimé, 9783642195877
• Statistical Pronunciation Modeling for Non-Native Speech Processing, Texte imprimé, 9783642268144
Description
Résumé:In this work, the authors present a fully statistical approach to model non--native speakers' pronunciation. Second-language speakers pronounce words in multiple different ways compared to the native speakers. Those deviations, may it be phoneme substitutions, deletions or insertions, can be modelled automatically with the new method presented here. The methods is based on a discrete hidden Markov model as a word pronunciation model, initialized on a standard pronunciation dictionary. The implementation and functionality of the methodology has been proven and verified with a test set of non-native English in the regarding accent. The book is written for researchers with a professional interest in phonetics and automatic speech and speaker recognition.
Description:Archives Springer e-books (Licence nationale)
Archives Springer e-books (Licence nationale)
ISBN:9783642195860
ISSN:1860-4870
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