Toward an Index of Oral Somatosensory Acuity: Comparison of Three Measures in Adults
Bibliographic record
Abstract
PURPOSE: Somatosensory targets and feedback are instrumental in ensuring accurate speech production. Individuals differ in their ability to access and respond to somatosensory information, but there is no established standard for measuring somatosensory acuity. The primary objective of this study was to determine which of three measures of somatosensory acuity had the strongest association with change in production accuracy in a vowel learning task, while controlling for the better-studied covariate of auditory acuity. METHOD: Three somatosensory tasks were administered to 20 female college students: an oral stereognosis task, a bite block task with auditory masking, and a novel phonetic awareness task. Individual scores from the tasks were compared to their performance on a speech learning task in which participants were trained to produce novel Mandarin vowels with visual biofeedback. RESULTS: Of the three tasks, only bite block adaptation with auditory masking was significantly associated with performance in the speech learning task. Participants with weaker somatosensory acuity tended to demonstrate larger increases in production accuracy over the course of training. CONCLUSIONS: The bite block adaptation task measures proprioceptive awareness rather than tactile acuity and assesses somatosensory knowledge implicitly, with limited metalinguistic demands. This small-scale study provides preliminary evidence that these characteristics may be desirable for the assessment of oral somatosensory acuity, at least in the context of vowel learning tasks. Well-normed somatosensory measures could be of clinical utility by informing diagnosis/prognosis and treatment planning.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".