Amazon cover image
Image from Amazon.com

Statistical Pronunciation Modeling for Non-Native Speech Processing [electronic resource] / by Rainer E. Gruhn, Wolfgang Minker, Satoshi Nakamura.

By: Contributor(s): Series: Signals and Communication TechnologyPublisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2011Description: X, 114 p. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783642195860
Subject(s): Genre/Form: Additional physical formats: Printed edition:: No titleDDC classification:
  • 621.382 23
LOC classification:
  • TK5102.9
  • TA1637-1638
  • TK7882.S65
Online resources:
Contents:
Introduction -- Automatic Speech Recognition -- Properties of Non-native Speech -- Pronunciation Variation Modeling in the Literature -- Non-native Speech Database -- Handling Non-native Speech -- Pronunciation HMMs.
In: Springer eBooksSummary: 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.
Item type: eBooks
Star ratings
    Average rating: 0.0 (0 votes)
No physical items for this record

Introduction -- Automatic Speech Recognition -- Properties of Non-native Speech -- Pronunciation Variation Modeling in the Literature -- Non-native Speech Database -- Handling Non-native Speech -- Pronunciation HMMs.

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.

Copyright © 2020 Alfaisal University Library. All Rights Reserved.
Tel: +966 11 2158948 Fax: +966 11 2157910 Email:
librarian@alfaisal.edu