A high-speed laryngoscopic investigation of aryepiglottic trilling
Bibliographic record
Abstract
Six aryepiglottic trills with varied laryngeal parameters were recorded using high-speed laryngoscopy to investigate the nature of the oscillatory behavior of the upper margin of the epilaryngeal tube. Image analysis techniques were applied to extract data about the patterns of aryepiglottic fold oscillation, with a focus on the oscillatory frequencies of the folds. The acoustic impact of aryepiglottic trilling is also considered, along with possible interactions between the aryepiglottic vibration and vocal fold vibration during the voiced trill. Overall, aryepiglottic trilling is deemed to be correctly labeled as a trill in phonetic terms, while also acting as a means to alter the quality of voicing to be auditorily harsh. In terms of its characterization, aryepiglottic vibration is considerably irregular, but it shows indications of contributing quasi-harmonic excitation of the vocal tract, particularly noticeable under conditions of glottal voicelessness. Aryepiglottic vibrations appear to be largely independent of glottal vibration in terms of oscillatory frequency but can be increased in frequency by increasing overall laryngeal constriction. There is evidence that aryepiglottic vibration induces an alternating vocal fold vibration pattern. It is concluded that aryepiglottic trilling, like ventricular phonation, should be regarded as a complex, if highly irregular, sound source.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".