Modeling the Biomechanical Influence of Epilaryngeal Stricture on the Vocal Folds: A Low-Dimensional Model of Vocal–Ventricular Fold Coupling
Bibliographic record
Abstract
PURPOSE Physiological and phonetic studies suggest that, at moderate levels of epilaryngeal stricture, the ventricular folds impinge upon the vocal folds and influence their dynamical behavior, which is thought to be responsible for constricted laryngeal sounds. In this work, the authors examine this hypothesis through biomechanical modeling. METHOD The dynamical response of a low-dimensional, lumped-element model of the vocal folds under the influence of vocal-ventricular fold coupling was evaluated. The model was assessed for F0 and cover-mass phase difference. Case studies of simulations of different constricted phonation types and of glottal stop illustrate various additional aspects of model performance. RESULTS Simulated vocal-ventricular fold coupling lowers F0 and perturbs the mucosal wave. It also appears to reinforce irregular patterns of oscillation, and it can enhance laryngeal closure in glottal stop production. CONCLUSION The effects of simulated vocal-ventricular fold coupling are consistent with sounds, such as creaky voice, harsh voice, and glottal stop, that have been observed to involve epilaryngeal stricture and apparent contact between the vocal folds and ventricular folds. This supports the view that vocal-ventricular fold coupling is important in the vibratory dynamics of such sounds and, furthermore, suggests that these sounds may intrinsically require epilaryngeal stricture.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".