Source Modeling Techniques for Quality Enhancement in Statistical Parametric Speech Synthesis

✍ Scribed by K. Sreenivasa Rao, N. P. Narendra

Publisher: Springer International Publishing
Year: 2019
Tongue: English
Leaves: 145
Series: SpringerBriefs in Speech Technology
Edition: 1st ed.
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

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.

✦ Table of Contents

Front Matter ....Pages i-xii
Introduction (K. Sreenivasa Rao, N. P. Narendra)....Pages 1-10
Background and Literature Review (K. Sreenivasa Rao, N. P. Narendra)....Pages 11-27
Robust Voicing Detection and F0 Estimation Method (K. Sreenivasa Rao, N. P. Narendra)....Pages 29-52
Parametric Approach of Modeling the Source Signal (K. Sreenivasa Rao, N. P. Narendra)....Pages 53-74
Hybrid Approach of Modeling the Source Signal (K. Sreenivasa Rao, N. P. Narendra)....Pages 75-103
Generation of Creaky Voice (K. Sreenivasa Rao, N. P. Narendra)....Pages 105-124
Summary and Conclusions (K. Sreenivasa Rao, N. P. Narendra)....Pages 125-129
Back Matter ....Pages 131-136

✦ Subjects

Engineering; Signal, Image and Speech Processing; Computational Linguistics

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