Predicting Prosody from Text for Text-to-Speech Synthesis, 2012 SpringerBriefs in Speech Technology Series

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.

Explores the intuitive relation between prosody and linguistic and production constraints

Proposes non-linear models such as neural networks and support vector machines for capturing the prosodic information from the linguistic and production constraints

Demonstrates the use of predicted prosodic knowledge for speech, speaker and language

Includes supplementary material: sn.pub/extras