Statistical Pronunciation Modeling for Non-Native Speech Processing
Language: English
Published by Springer Berlin Heidelberg, 2013
Series: Book 44 of 180 - Signals and Communication Technology
- Softcover
- New
Condition: New
£ 80.29
Quantity: Over 20 available
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Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents a new methodology for speech recognition of non-native speakersShows a proven and verified approachIn this work, the authors present a fully statistical approach to model non--native speakers pronunciation. Second-language spe.
Seller Inventory # 5054858
- Title
- Statistical Pronunciation Modeling for Non-Native Speech Processing
- Author
- Rainer E. Gruhn|Wolfgang Minker|Satoshi Nakamura
- Publisher
- Springer Berlin Heidelberg
- Publication year
- 2013
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 10
- 3642268145
- ISBN 13
- 9783642268144
- Series
- Book 44 of 180: Signals and Communication Technology
- Seller catalogs
- Mathematik/Naturwissenschaften/Technik/Medizin
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.
"Synopsis" may belong to another edition of this title.
From the Back Cover
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.
"About the title" may belong to another edition of this title.
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