Cross-Linguistic Bracing : Analyzing Vertical Tongue Movement
Bibliographic record
Abstract
Bracingdescribes a tongue posture in which the tongue is in contact with the vocal tract surface. Lateral bracing,in particular, refers to when the sides of the tongue contact the roof of the mouth, along either the upper molars or hard palate. Previous research has found evidence of lateral bracing in six native speakers of different languages [Cheng et al. 2017. Canadian Acoustics, 45(3), 186-187]. The current study examines lateral bracing cross-linguistically at a larger scale using ultrasound technology to image tongue movement. We tracked and measured the magnitude of vertical tongue movement at three positions (left, right, and middle) over time using Flow Analyzer [Barbosa, 2014. J Acoust Soc Am, 136(4), 2105-2105]. Preliminary results across all six languages, including Cantonese, English, French, Korean, Mandarin and Spanish, show that the sides of the tongue are more stable than the center and stays at a relatively high position in the mouth. The magnitude of movement at the sides are significantly smaller than the center of the tongue. Further, releases of the sides vary in frequency for different languages. Taken together, this gives evidence that bracing is a physiological fact about speech production irrespective of the language spoken.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".