Perceptual calibration of <i>F</i>0 production: Evidence from feedback perturbation
Bibliographic record
Abstract
Hearing one's own speech is important for language learning and maintenance of accurate articulation. For example, people with postlinguistically acquired deafness often show a gradual deterioration of many aspects of speech production. In this manuscript, data are presented that address the role played by acoustic feedback in the control of voice fundamental frequency (F0). Eighteen subjects produced vowels under a control (normal F0 feedback) and two experimental conditions: F0 shifted up and F0 shifted down. In each experimental condition subjects produced vowels during a training period in which their F0 was slowly shifted without their awareness. Following this exposure to transformed F0, their acoustic feedback was returned to normal. Two effects were observed. Subjects compensated for the change in F0 and showed negative aftereffects. When F0 feedback was returned to normal, the subjects modified their produced F0 in the opposite direction to the shift. The results suggest that fundamental frequency is controlled using auditory feedback and with reference to an internal pitch representation. This is consistent with current work on internal models of speech motor control.
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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 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".