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Related Experiment Videos

Speech synthesis by glottal excited linear prediction

D G Childers1, H T Hu

  • 1Department of Electrical Engineering, University of Florida, Gainesville 32611-2024.

The Journal of the Acoustical Society of America
|October 1, 1994
PubMed
Summary

Quantizing glottal excitation waveforms does not degrade speech quality in the new glottal excitation linear predictive (GELP) synthesizer. This method offers high-quality speech synthesis with potential for voice analysis and modification.

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Area of Science:

  • Speech synthesis
  • Digital signal processing
  • Acoustic phonetics

Background:

  • Linear predictive (LP) speech synthesis is a common technique.
  • Modeling glottal excitation is crucial for realistic speech synthesis.
  • Existing methods may not fully capture glottal waveform nuances.

Purpose of the Study:

  • To demonstrate that quantizing the glottal excitation waveform does not significantly degrade synthesized speech quality.
  • To introduce a novel Glottal Excitation Linear Predictive (GELP) synthesizer.
  • To explore the potential of a codebook-based glottal excitation model.

Main Methods:

  • Developed a 6th-order polynomial waveform model for glottal excitation.
  • Designed and trained a 32-entry glottal excitation codebook for voiced sounds.

Related Experiment Videos

  • Utilized a 256-entry stochastic codebook for unvoiced noise excitation.
  • Implemented a GELP synthesizer based on pitch-excited LP and CELP coder principles.

    • Main Results:

    • The GELP synthesizer resynthesizes speech with high quality.
    • Quantization of the glottal excitation waveform showed minimal impact on speech quality.
    • The excitation model waveform relates to the derivative of glottal flow and integral of the residue.

    Conclusions:

    • The GELP synthesizer offers a simple, high-quality speech synthesis procedure.
    • The approach can reproduce all speech sounds using established analysis techniques.
    • The glottal excitation codebook enables quantitative comparison of different voice types and potential voice conversion.