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Synthetic, Multi-Layer, Self-Oscillating Vocal Fold Model Fabrication
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Published on: December 2, 2011

Sinusoidal modeling for nonstationary voiced speech based on a local vector transform.

Masashi Ito1, Masafumi Yano

  • 1Research Institute of Electrical Communication, Tohoku University, 2-1-1 Katahira, Aoba-ku, Sendai 980-8577, Japan.

The Journal of the Acoustical Society of America
|April 6, 2007
PubMed
Summary

A new local vector transform (LVT) method accurately determines instantaneous frequency and amplitude for nonstationary voiced speech signals. This approach overcomes limitations of traditional methods by not assuming local stationarity, improving speech analysis.

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Area of Science:

  • Speech processing
  • Signal analysis
  • Acoustics

Background:

  • Voiced speech signals are complex, composed of time-varying sinusoidal components.
  • Traditional analysis methods often assume signal stationarity within local segments, leading to errors.
  • Accurate determination of instantaneous frequency and amplitude is crucial for understanding speech dynamics.

Purpose of the Study:

  • To introduce a novel method, the local vector transform (LVT), for analyzing nonstationary sinusoids in voiced speech.
  • To evaluate the effectiveness of LVT in determining instantaneous frequency and amplitude without assuming local stationarity.
  • To compare LVT's performance against existing speech analysis algorithms.

Main Methods:

  • Development of the local vector transform (LVT) algorithm.
  • Application of LVT to synthesized and naturally uttered speech signals.
  • Comparative analysis of LVT with time-corrected instantaneous frequency, spectral peak-picking, autocorrelation, and cepstrum methods.

Main Results:

  • LVT determined instantaneous frequency with accuracy comparable to the time-corrected instantaneous frequency method.
  • LVT significantly outperformed spectral peak-picking, autocorrelation, and cepstrum in frequency determination.
  • LVT accurately determined instantaneous amplitude, while other methods exhibited considerable errors.
  • Reconstructed speech signals using LVT parameters showed high agreement with original components.

Conclusions:

  • The local vector transform (LVT) is an effective method for analyzing time-varying parameters of voiced speech signals.
  • LVT overcomes the limitations of stationarity assumptions in traditional speech analysis.
  • The method offers improved accuracy for both instantaneous frequency and amplitude estimation in nonstationary speech.