Source Modeling Techniques for Quality Enhancement in Statistical Parametric Speech Synthesis

• Κύριοι συγγραφείς: Rao, K. Sreenivasa (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut), Narendra, N. P. (http://id.loc.gov/vocabulary/relators/aut)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2019.
• Έκδοση: 1st ed. 2019.
• Σειρά: SpringerBriefs in Speech Technology, Studies in Speech Signal Processing, Natural Language Understanding, and Machine Learning,
• Θέματα: Signal processing.; Image processing.; Speech processing systems.; Natural language processing (Computer science).; Computational linguistics.; Signal, Image and Speech Processing.; Natural Language Processing (NLP).; Computational Linguistics.

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...

Πίνακας περιεχομένων:

• Chapter 1. Introduction
• Chapter 2. Background and literature review
• Chapter 3. Robust voicing detection and F0 estimation method
• Chapter 4. Parametric approach of modeling the source signal
• Chapter 5. Hybrid approach of modeling the source signal
• Chapter 6. Generation of creaky voice
• Chapter 7. Summary and conclusions.