Overview
- Presents the efficient excitation source modeling techniques for generating high quality speech
- Includes a combination of both waveform and parametric methods to enhance the quality of synthesis
- Features and methods that need less memory and computational requirements than others, allowing them to be integrated to smart phones and smaller devices
Part of the book series: SpringerBriefs in Speech Technology (BRIEFSSPEECHTECH)
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About this book
This book presents a statistical parametric speech synthesis (SPSS) framework for developing a speech synthesis system where the desired speech is generated from the parameters of vocal tract and excitation source. Throughout the book, the authors discuss novel source modeling techniques to enhance the naturalness and overall intelligibility of the SPSS system. This book provides several important methods and models for generating the excitation source parameters for enhancing the overall quality of synthesized speech. The contents of the book are useful for both researchers and system developers. For researchers, the book is useful for knowing the current state-of-the-art excitation source models for SPSS and further refining the source models to incorporate the realistic semantics present in the text. For system developers, the book is useful to integrate the sophisticated excitation source models mentioned to the latest models of mobile/smart phones.
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Keywords
Table of contents (7 chapters)
Authors and Affiliations
About the authors
K. Sreenivasa Rao is currently a Professor at IIT Kharagpur, where he has taught since 2007. He has also worked at IIT Guwahati and IIT Madras. He received his PhD from IIT Madras in 2005. He is the author of 8 books, 68 journal articles, 2 patents, 25 book chapters, and 140 conference proceedings.
Narendra N P is a Postdoctoral Researcher at Aalto University. He received his PhD at IIT Kharagpur in 2016. He has published 7 journal articles, 3 book chapters, and 15 conference proceedings.
Bibliographic Information
Book Title: Source Modeling Techniques for Quality Enhancement in Statistical Parametric Speech Synthesis
Authors: K. Sreenivasa Rao, N. P. Narendra
Series Title: SpringerBriefs in Speech Technology
DOI: https://doi.org/10.1007/978-3-030-02759-9
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: The Author(s), under exclusive licence to Springer Nature Switzerland AG 2019
Softcover ISBN: 978-3-030-02758-2Published: 28 January 2019
eBook ISBN: 978-3-030-02759-9Published: 13 December 2018
Series ISSN: 2191-737X
Series E-ISSN: 2191-7388
Edition Number: 1
Number of Pages: XII, 136
Number of Illustrations: 63 b/w illustrations, 11 illustrations in colour
Topics: Signal, Image and Speech Processing, Natural Language Processing (NLP), Computational Linguistics