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Updated: Aug 31, 2025
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Hemi-laryngeal Setup for Studying Vocal Fold Vibration in Three Dimensions
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Sensitivity of Source-Filter Interaction to Specific Vocal Tract Shapes
Ingo R Titze1, Anil Palaparthi2
1National Center for Voice and Speech, University of Utah, Salt Lake City, UT 84101 USA; Department of Communication Sciences and Disorders, University of Iowa, Iowa City, IA 52242 USA.
IEEE/ACM Transactions on Audio, Speech, and Language Processing
|August 22, 2022
Summary
Vocal tract narrowing significantly impacts voice production by altering aero-acoustic and tissue movement interactions. Key laryngeal regions are most sensitive to these changes, affecting voice quality.
Area of Science:
- Acoustic phonetics
- Bioengineering
- Computational fluid dynamics
Background:
- Source-filter theory describes voice production as a source (larynx) and filter (vocal tract).
- Understanding vocal tract aerodynamics is crucial for diagnosing and treating voice disorders.
Purpose of the Study:
- To computationally quantify the effects of vocal tract geometry on source-filter interaction.
- To identify vocal tract segments most sensitive to acoustic variations.
Main Methods:
- One-dimensional Navier-Stokes (transmission line) model used for aero-acoustic (Level 1) and tissue movement (Level 2) interactions.
- Systematic variation of vocal tract segment length and cross-sectional area.
- Quantification of glottal airflow, flow declination rate, formant ripple, glottal area, phonation threshold pressure, and frequency deviation.
Main Results:
- Acoustic variables are most sensitive to variations in the ventricle, false-fold glottis, conus elasticus entry, and laryngeal vestibule.
- Narrowing of vocal tract segments increases source-filter interaction.
- Proximity of narrow segments to the vocal folds amplifies their effect.
Conclusions:
- Specific laryngeal structures play a critical role in vocal tract acoustics.
- Vocal tract geometry significantly modulates voice production through aero-acoustic and tissue interactions.
- Computational modeling provides valuable insights into voice production mechanisms.
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