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Title page for etd-0104108-100045


URN etd-0104108-100045 Statistics This thesis had been viewed 2298 times. Download 18 times.
Author Yu-liang Hsueh
Author's Email Address No Public.
Department Computer Science and Enginerring
Year 2007 Semester 1
Degree Master Type of Document Master's Thesis
Language zh-TW.Big5 Chinese Page Count 41
Title The Research and Application of Chinese Speech Synthesis Based on Hidden Markov Model
Keyword
  • Text-to-Speech synthesis system
  • speech reconstruction
  • Hidden Markov model
  • Hidden Markov model
  • speech reconstruction
  • Text-to-Speech synthesis system
  • Abstract This thesis describes a novel approach to text-to-speech synthesis (TTS)
    based on hidden Markov model (HMM). There have been several attempts
    proposed to utilize HMM for constructing TTS systems.
    However, most of such systems are based on waveform concatenation techniques.
    In the proposed approach, we constructs this TTS system based on the speech parameter to complete the goal of the map navigation.
    We get the speech parameter sequences that generated from HMM directly based on maximum likelihood criterion.
    By considering relationship between static and dynamic parameters, smooth spectral sequences are generated according to the statistics of static and dynamic parameters
    modeled by HMMs.
    As a result, natural sounding speech can be synthesized throught speech reconstruction technique.
    Advisor Committee
  • Tai-wen Yue - advisor
  • Chen-Chiung Hsieh - co-chair
  • none - co-chair
  • Files indicate in-campus access only
    Date of Defense 2008-01-02 Date of Submission 2008-01-04


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