Phonemic processing in compensatory responses of French and English speakers to formant shifted auditory feedback
Bibliographic record
Abstract
Past studies have shown that speakers modify their vowel formant production when auditory feedback is altered in order to make the feedback more consistent with the intended sound. This behavior was thought to minimize acoustic error overall; however, Mitsuya et al. (2011) showed different magnitudes of compensation for altered F1 across two language groups depending on the direction of perturbation. Their results seem to reflect how the target vowel is represented in relation to other vowels around it. From this observation, they proposed that compensation is to maintain perceptual identity of the produced vowel, requiring some phonological processes for error reduction. Yet, the results might have been specific to the language groups examined, and/or unique to F1 production. To generalize Mitsuya et al.’s hypothesis, the current study examined 1) different language groups and 2) F2 production. We compared compensatory behavior of F2 for /ɛ/ among French speakers (FRN) and English speakers (ENG) with decreased F2 feedback. With this perturbation, the feedback sounded like /œ/, which is phonemic in French but not in English. The preliminary data suggest that FRN compensated in response to smaller perturbations and showed greater maximum compensations than ENG.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".