Predicting Prosody from Text for Text-to-Speech Synthesis

  • K. Sreenivasa Rao

Part of the SpringerBriefs in Electrical and Computer Engineering book series

Also part of the SpringerBriefs in Speech Technology book sub series (BRIEFSSPEECHTECH)

Table of contents

  1. Front Matter
    Pages i-xii
  2. K. Sreenivasa Rao
    Pages 1-6
  3. K. Sreenivasa Rao
    Pages 7-25
  4. K. Sreenivasa Rao
    Pages 27-39
  5. K. Sreenivasa Rao
    Pages 41-63
  6. K. Sreenivasa Rao
    Pages 65-75
  7. K. Sreenivasa Rao
    Pages 77-96
  8. K. Sreenivasa Rao
    Pages 97-111
  9. K. Sreenivasa Rao
    Pages 113-116
  10. Back Matter
    Pages 117-130

About this book


Predicting Prosody from Text for Text-to-Speech Synthesis covers the specific aspects of prosody, mainly focusing on how to predict the prosodic information from linguistic text, and then how to exploit the predicted prosodic knowledge for various speech applications. Author K. Sreenivasa Rao discusses proposed methods along with state-of-the-art techniques for the acquisition and incorporation of prosodic knowledge for developing speech systems.

Positional, contextual and phonological features are proposed for representing the linguistic and production constraints of the sound units present in the text. This book is intended for graduate students and researchers working in the area of speech processing.


Duration Epochs Glottal closure instants Intonation Linguistic constraints Neural networks Non-linear models Pitch Production constraints Prosody Prosody modification Support vector machines Text-to-speech synthesis Time scale modification

Authors and affiliations

  • K. Sreenivasa Rao
    • 1
  1. 1., School of Information TechnologyIndian Institute of TechnologyKharagpurIndia

Bibliographic information

  • DOI
  • Copyright Information Springer Science+Business Media New York 2012
  • Publisher Name Springer, New York, NY
  • eBook Packages Engineering
  • Print ISBN 978-1-4614-1337-0
  • Online ISBN 978-1-4614-1338-7
  • Series Print ISSN 2191-8112
  • Series Online ISSN 2191-8120
  • Buy this book on publisher's site
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