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GMM Classification of Text-to-Speech Synthesis: Identification of Original Speaker’s Voice

  • Jiří Přibil
  • Anna Přibilová
  • Jindřich Matoušek
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8655)

Abstract

This paper describes two experiments. The first one deals with evaluation of synthetic speech quality by reverse identification of original speakers whose voices had been used for several Czech text-to-speech (TTS) systems. The second experiment was aimed at evaluation of the influence of voice transformation on the original speaker recognition. The paper further describes an analysis of the influence of initial settings for creation and training of the Gaussian mixture models (GMM), and the influence of different types of used speech features (spectral and/or supra-segmental) on correctness of GMM identification. The stability of the identification process with respect to the duration of the tested sentence (number of the processed frames) was analysed, too.

Keywords

quality of synthetic speech text-to-speech system GMM classification statistical analysis 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Jiří Přibil
    • 1
    • 2
  • Anna Přibilová
    • 3
  • Jindřich Matoušek
    • 1
  1. 1.Faculty of Applied Sciences, Dept. of CyberneticsUniversity of West BohemiaPlzeňCzech Republic
  2. 2.Institute of Measurement ScienceSASBratislavaSlovakia
  3. 3.Faculty of Electrical Engineering & Information Technology, Institute of Electronics and PhotonicsSlovak University of TechnologyBratislavaSlovakia

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