Compensation strategies for a lip-tube perturbation of French [u]: An acoustic and perceptual study of 4-year-old children
Bibliographic record
Abstract
The relations between production and perception in 4-year-old children were examined in a study of compensation strategies for a lip-tube perturbation. Acoustic and perceptual analyses of the rounded vowel [u] produced by twelve 4-year-old French speakers were conducted under two conditions: normal and with a 15-mm-diam tube inserted between the lips. Recordings of isolated vowels were made in the normal condition before any perturbation (N1), immediately upon insertion of the tube and for the next 19 trials in this perturbed condition, with (P2) or without articulatory instructions (P1), and in the normal condition after the perturbed trials (N2). The results of the acoustic analyses reveal speaker-dependent alterations of F1, F2, and/or F0 in the perturbed conditions and after the removal of the tube. For some subjects, the presence of the tube resulted in very little change; for others, an increase in F2 was observed in P1, which was generally reduced in some of the 20 repetitions, but not systematically and not continuously. The use of articulatory instructions provided in the P2 condition was detrimental to the achievement of a good acoustic target. Perceptual data are used to determine optimal combinations of F0, F1, and F2 (in bark) related to these patterns. The data are compared to a previous study conducted with adults [Savariaux et al., J. Acoust. Soc. Am. 106, 381-393 (1999)].
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".