Vowel production in sighted adults and blind adults: A study of speech adaptation strategies in high-intensity background noise
Bibliographic record
Abstract
Recent studies have shown that congenitally blind speakers have greater auditory discrimination acuity than sighted speakers [Ménard, Dupont, Baum, and Aubin, J. Acoust. Soc. Am. 126, 1404–1414 (2009)]. At the production level, however, blind speakers produce smaller displacements of the lips (visible articulator) than their sighted peers. In order to further investigate the impact of visual experience on the articulatory gestures used to produce intelligible speech, adaptation strategies in background noise was studied in blind and sighted speakers. Ten sighted and 10 congenitally blind adult French participants were recorded during the production of the vowels /i/, /y/, /u/, /a/ in a CVC context. Two conditions were elicited: with high-intensity noise heard through headphones and without noise. Synchronous acoustic and articulatory data were recorded using the Carstens AG500 Electromagnetic Articulograph system. Formant measures and movements of the lips and tongue were analyzed. Results reveal that blind speakers produced smaller ranges of lip movement than sighted speakers in the noisy condition, suggesting that the blind subjects made less use of visible articulators to improve intelligibility. Results are discussed in light of multimodal production-perception relationships in speech.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".