Three-dimensional finite element acoustic analysis of bent vocal tracts
Bibliographic record
Abstract
The bent air column in a vocal tract can significantly impact its acoustic characteristics by altering formant frequencies. However, existing vocal tract models typically assume the tract to be a straight three-dimensional (3D) tube with varying cross-sectional areas. Although wave propagation in realistic vocal tracts has been previously studied, the acoustic effect of the tract curvature on resonance frequencies has yet to be thoroughly explored. In this work, we use a state-of-the-art 3D finite element (FE) wave solver to characterize the effect of bending in acoustic ducts, akin to vocal tracts, by comparing their transfer functions up to 14 kHz. The duct geometries are modified to match vocal tracts for vowels /a/ and /u/. For a comparative analysis, we empirically adjust the degree of bending for a portion of the duct to increase its geometrical complexity. Our result shows that the bent air column does not significantly affect acoustic output for ducts with uniform cross-sections. However, transverse modes appear at higher frequencies for bent vocal tract geometries, i.e., ducts with varying cross-sectional areas. The comparison of transfer functions also shows that above 7 kHz, there is a notable shift in formant frequencies for such duct geometries.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".