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Related Experiment Videos

The shift-invariant discrete wavelet transform and application to speech waveform analysis.

Jörg Enders1, Weihua Geng, Peijun Li

  • 1Department of Mathematics, Michigan State University, East Lansing, Michigan 48824-1027, USA.

The Journal of the Acoustical Society of America
|May 19, 2005
PubMed
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A new discrete wavelet transform algorithm offers shift invariance for analyzing and editing nonstationary waveforms. This signal processing technique enables click-free audio editing and preserves original sound characteristics.

Area of Science:

  • Signal Processing
  • Wavelet Theory
  • Digital Audio

Background:

  • Nonstationary, time-sampled waveforms require advanced analysis tools.
  • The discrete wavelet transform (DWT) is a powerful signal processing technique.
  • Shift invariance is a desirable but computationally challenging property for DWT.

Purpose of the Study:

  • To present a new, easily implementable algorithm for the pseudoinverse of a shift-invariant DWT.
  • To demonstrate the utility of this shift-invariant transform for waveform visualization and editing.
  • To showcase applications in speech signal analysis and manipulation.

Main Methods:

  • Developed a novel algorithm for the pseudoinverse of the shift-invariant discrete wavelet transform.
  • Implemented the algorithm in array-oriented scripting languages.

Related Experiment Videos

  • Applied the transform to analyze and edit a recorded speech waveform.

    • Main Results:

    • The new algorithm provides shift invariance with a pseudoinverse, simplifying implementation.
    • Visualization revealed detailed speech characteristics like glottal modulation and waveform irregularities.
    • Waveform editing, including speed alteration, was performed in the wavelet domain, preserving pitch and formant frequencies and producing click-free results.

    Conclusions:

    • The shift-invariant discrete wavelet transform with pseudoinvertibility is a valuable tool for signal processing.
    • This technique enhances waveform visualization and enables precise, artifact-free audio editing.
    • The method preserves essential acoustic properties, leading to clear and understandable modified speech.