Formant compensation for auditory feedback with English vowels
Bibliographic record
Abstract
Past studies have shown that speakers spontaneously adjust their speech acoustics in response to their auditory feedback perturbed in real time. In the case of formant perturbation, the majority of studies have examined speaker's compensatory production using the English vowel /ɛ/ as in the word "head." Consistent behavioral observations have been reported, and there is lively discussion as to how the production system integrates auditory versus somatosensory feedback to control vowel production. However, different vowels have different oral sensation and proprioceptive information due to differences in the degree of lingual contact or jaw openness. This may in turn influence the ways in which speakers compensate for auditory feedback. The aim of the current study was to examine speakers' compensatory behavior with six English monophthongs. Specifically, the current study tested to see if "closed vowels" would show less compensatory production than "open vowels" because closed vowels' strong lingual sensation may richly specify production via somatosensory feedback. Results showed that, indeed, speakers exhibited less compensatory production with the closed vowels. Thus sensorimotor control of vowels is not fixed across all vowels; instead it exerts different influences across different vowels.
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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 | 0.000 | 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) | 0.001 | 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".