Vowel production and perception in French blind and sighted adults
Bibliographic record
Abstract
It is well known that visual cues play an important role in speech perception and production. Early in life, blind speakers, who do not have access to visual information related to lip and jaw movements, show a delay in the acquisition of phonological contrasts based on these visible articulatory features [A. E. Mills, Hearing by eye: The psychology of lip-reading, pp. 145–161 (1987)]. It has also been claimed that blind speakers have better auditory discrimination abilities than sighted speakers. The goal of this study is to describe the production-perception relationships involved in French vowels for blind and sighted speakers. Six blind adults and six sighted adults served as subjects. The auditory abilities of each subject were evaluated by auditory discrimination tests (AXB). At the production level, ten repetitions of the ten French oral vowels were recorded. Formant values and fundamental frequency values were extracted from the acoustic signal. Measures of contrasts (Euclidean distances) and dispersion (standard deviations) were computed and compared for each feature (height, place, roundedness) and group (blind, sighted). Regression analyses between discrimination scores and produced contrasts were carried out. Despite between-speaker variability, results show an effect of speakers group (blind versus sighted) on the produced contrast distances.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".