Glottal Waves via Inverse Filtering of Vowel Sounds
Bibliographic record
Abstract
This paper shows how to obtain accurate glottal waves via inverse filtering of vowel sounds and how to determine if these glottal waves contain any significant resonance of vocal tracts. We obtain vocal-tract filter (VTF) estimates for the inverse filtering from sustained vowel sounds over closed glottal phases using a new method, which minimizes the effects of glottal waves on the VTF estimates. It is common that VTF estimates contain the effects of incomplete glottal closures, and the glottal waves obtained via inverse filtering contain residual vocal-tract resonance. Our simulations show that the residual resonance appears as stationary ripples superimposed on the derivatives of the original glottal waves over the duration of a glottal cycle. The VTF estimates and the glottal waves obtained from sustained vowel sounds /a/ produced by male and female subjects are presented. The derivatives of the obtained glottal waves exhibit transient positive peaks during vocal-fold collision and negative levels in the earlier stage of vocal-fold parting.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".