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Predicting Prosody from Text for Text-to-Speech SynthesisProsody Knowledge for Speech Systems: A Review

Predicting Prosody from Text for Text-to-Speech Synthesis: Prosody Knowledge for Speech Systems:... [This chapter provides an overview of some of the existing models for acquisition of prosody and also methods for incorporating the prosody in speech signal. The models used for capturing the prosody range from rule-based models to data-based models. Rule-based models often generalize too much and can not handle exceptions well. Data-based models are generally dependent on the quality and quantity of the data available. At the end of the chapter motivation for the present work in this book is derived from the limitations of the existing works.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Predicting Prosody from Text for Text-to-Speech SynthesisProsody Knowledge for Speech Systems: A Review

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Publisher
Springer New York
Copyright
© Springer Science+Business Media New York 2012
ISBN
978-1-4614-1337-0
Pages
7 –25
DOI
10.1007/978-1-4614-1338-7_2
Publisher site
See Chapter on Publisher Site

Abstract

[This chapter provides an overview of some of the existing models for acquisition of prosody and also methods for incorporating the prosody in speech signal. The models used for capturing the prosody range from rule-based models to data-based models. Rule-based models often generalize too much and can not handle exceptions well. Data-based models are generally dependent on the quality and quantity of the data available. At the end of the chapter motivation for the present work in this book is derived from the limitations of the existing works.]

Published: Mar 27, 2012

Keywords: Discrete Cosine Transform; Speech Signal; Indian Language; Pitch Accent; Intonational Phrase

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