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Autor(en): 
  • K. Sreenivasa Rao
  • N. P. Narendra
  • Source Modeling Techniques for Quality Enhancement in Statistical Parametric Speech Synthesis 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 2 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 5-10 Tagen versandfertig
    Veröffentlichung:  Januar 2019  
    Genre:  Naturwissensch., Medizin, Technik 
    ISBN:  9783030027582 
    EAN-Code: 
    9783030027582 
    Verlag:  Springer International Publishing 
    Einband:  Kartoniert  
    Sprache:  English  
    Serie:  SpringerBriefs in Speech Technology  
    Dimensionen:  H 235 mm / B 155 mm / D 9 mm 
    Gewicht:  236 gr 
    Seiten:  148 
    Zus. Info:  Paperback 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    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.
    • 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.

      



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