Cross-linguistic lateral bracing: An ultrasound study
Bibliographic record
Abstract
Lateral bracing refers to intentional stabilizing of tongue contact with the roof of the mouth along the upper molars or the hard palate. Previous research has found evidence of lateral bracing in individual speakers of six languages [Cheng et al. 2017. Can. Acoust. 45, 186]. 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) in the coronal plane over time using Flow Analyzer [Barbosa, 2014. J. Acoust. Soc. Am. 136, 2105] for optical flow analysis. Preliminary results across all languages (Cantonese, English, French, Korean, Mandarin, and Spanish) show that the sides of the tongue are more stable than the center and maintain a relatively high position in the mouth throughout speech. The magnitude of movement at the sides is significantly smaller than at the center of the tongue. Further, lateral releases vary in frequency for different languages. This evidence supports the view that bracing is a physiological property of speech production that occurs irrespective of the language spoken. [Funding from NSERC.]
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".