Source modeling techniques for quality enhancement in statistical parametric speech synthesis /
[Book]
K. Sreenivasa Rao, N.P. Narendra.
Cham :
Springer,
[2019]
1 online resource (145 pages)
SpringerBriefs in Speech Technology
Includes bibliographical references and index.
Intro; Preface; Contents; Acronyms; 1 Introduction; 1.1 Introduction; 1.2 Speech Synthesis Methods; 1.2.1 Formant Synthesis; 1.2.2 Articulatory Synthesis; 1.2.3 Concatenative Synthesis; 1.2.4 Statistical Parametric Speech Synthesis; 1.2.5 Hybrid Synthesis Methods; 1.3 Objectives and Scope of the Work; 1.4 Contributions of the Book; 1.4.1 Robust Voicing Detection and F0 Estimation Method; 1.4.2 Parametric Approach of Modeling the Excitation Signal; 1.4.3 Hybrid Approach of Modeling the Excitation Signal; 1.4.4 Generation of Creaky Voice; 1.5 Organization of the Book; References
2 Background and Literature Review2.1 HMM-Based Speech Synthesis; 2.1.1 Hidden Markov Model; 2.1.2 System Overview; 2.1.3 Duration Modeling; 2.1.4 Decision Tree-Based Context Clustering; 2.1.5 Synthesis; 2.2 Voicing Detection and F0 Estimation: A Review; 2.3 Source Modeling Approaches: A Review; 2.4 Generation of Creaky Voice: A Review; 2.5 Summary; References; 3 Robust Voicing Detection and F0 Estimation Method; 3.1 F0 Modeling and Generation in HTS; 3.2 Proposed Method for Voicing Detection and F0 Estimation
3.2.1 Zero-Frequency Filtering Method for Detecting the Instants of Significant Excitation3.2.2 Voicing Detection; 3.2.3 Influence of Window Size on the Strength of Excitation; 3.2.4 F0 Estimation; 3.2.5 Performance Evaluation; 3.3 Implementation of the Proposed Voicing Detection and F0 Extraction in HTS Framework; 3.4 Evaluation; 3.4.1 Evaluation of Voicing Detection; 3.4.2 Subjective Evaluation; 3.5 Summary; References; 4 Parametric Approach of Modeling the Source Signal; 4.1 Parametric Source Modeling Method Based on Principal Component Analysis
4.1.1 Generation of Pitch-Synchronous Residual Frames4.1.2 Parameterization of Residual Frame Using PCA; 4.1.3 Speech Synthesis Using the Proposed PCA-Based Parametric Source Model; 4.1.4 Evaluation; 4.2 Parametric Source Modeling Method Based on the Deterministic and Noise Components of Residual Frames; 4.2.1 Analysis of Characteristics of Residual Frames; 4.2.2 Overview of Proposed Parametric Source Model; 4.2.3 Parameterization of Deterministic Component; 4.2.4 Parameterization of Noise Component
4.2.5 Speech Synthesis Using the Proposed Deterministic and Noise Component-Based Parametric Source Model4.2.6 Evaluation; 4.3 Summary; References; 5 Hybrid Approach of Modeling the Source Signal; 5.1 Optimal Residual Frame-Based Hybrid Source Modeling Method; 5.1.1 Computation of Optimal Residual Frame for a Phone; 5.1.2 Clustering the Optimal Residual Frames; 5.1.3 Speech Synthesis Using the Proposed Optimal Residual Frame-Based Hybrid Source Model; 5.1.4 Evaluation; 5.2 Time-Domain Deterministic Plus Noise Model-Based Hybrid Source Model
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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.
Springer Nature
com.springer.onix.9783030027599
Source Modeling Techniques for Quality Enhancement in Statistical Parametric Speech Synthesis.