Effects of Speaking Rate on the Control of Vocal Fold Vibration
Bibliographic record
Abstract
Stevens (1991) has suggested that, while speakers control glottal apertures in producing consonants, the buildup of intraoral pressure during an oral closure creates decreases in transglottal flow, which can, in itself, reduce or halt vocal fold vibrations. The object of this study was to determine whether speakers can take advantage of such pressure effects in controlling the voicing attributes of intervocalic stops. Intraoral pressure, vocal fold vibration (Lx portions of electroglottograms), and electromyographic (EMG) activity of the orbicularis oris inferior were monitored for 6 subjects while they produced at "slow," "normal," and "fast" speaking rates utterances containing intervocalic stops /p/ and /b/. Product-moment correlations between the intervocalic pressure rises and the amplitude contour of Lx showed strong negative relationships at normal-to-fast rates of speech. However, this relationship was not maintained at slower rates, where decreases in the amplitude of Lx sometimes occurred before the onset of EMG activity in the labial adductor. The findings suggest that, at normal-to-fast rates of speech, speakers can use the passive effects of pressure in controlling vocal fold vibration for stop consonants.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".