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Related Experiment Videos

Rules for controlling low-dimensional vocal fold models with muscle activation.

Ingo R Titze1, Brad H Story

  • 1National Center of Voice and Speech, and Department of Speech Pathology and Audiology, The University of Iowa, Iowa City 52242, USA. ingo-titze@uiowa.edu

The Journal of the Acoustical Society of America
|September 24, 2002
PubMed
Summary

This study presents a low-dimensional vocal fold model capturing shear and compressional vibration modes. The model accurately predicts vocal fold oscillation regions based on muscle activation, aligning with human subject data.

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Area of Science:

  • Biomechanics of speech production
  • Vocal fold dynamics modeling

Background:

  • Understanding vocal fold vibration is crucial for speech production.
  • Existing models often simplify the complex biomechanics of vocal folds.

Purpose of the Study:

  • To develop a low-dimensional, self-oscillation model of vocal folds.
  • To incorporate body-cover tissue differentiation and reconcile lumped-element with continuum mechanics.
  • To investigate the influence of muscle activation on vocal fold vibration modes.

Main Methods:

  • A low-dimensional model simulating shear and compressional vibration modes.
  • Implementation using masses, a rotating plate, and a bar mass for body-cover differentiation.
  • Control via normalized activation levels of cricothyroid (CT), thyroarytenoid (TA), lateral cricoarytenoid (LCA), and posterior cricoarytenoid (PCA) muscles, and lung pressure.

Related Experiment Videos

  • Empirically derived rules to convert muscle activity into physical vocal fold properties.

    • Main Results:

    • The model captures three primary vibration modes: one shear and two compressional.
    • It allows for anatomical body-cover differentiation of vocal fold tissues.
    • Oscillation regions in muscle activation control spaces closely resemble those measured in human subjects.

    Conclusions:

    • The developed low-dimensional model effectively simulates vocal fold self-oscillation.
    • It provides insights into the relationship between muscle activation and vocal fold vibration patterns.
    • The model offers a valuable tool for studying voice production biomechanics.