Psychophysical detection threshold of formant manipulations during speech production
Bibliographic record
Abstract
In altered auditory feedback experiments, participants respond rapidly and alter their speech production to compensate for the induced auditory feedback error. This response does not occur with small feedback perturbations, and thus there must be a threshold for compensation by the auditory-vocal feedback system. What is unknown is the psychophysical threshold during speech production (i.e., how large are manipulations that are consciously detectable?). The purpose of this experiment was to compare the threshold for conscious awareness of perturbation, and the minimal change that induces compensation. A real-time auditory feedback manipulation system was employed in a repeated measures design. The compensation threshold was determined using the change point test during a perturbation ramp of 4 Hz/utterance. In the psychophysical measurement, the size of the feedback manipulation followed a two-alternative forced-choice paradigm. With 17 individuals, the mean psychophysical threshold was 105 Hz (SE: 9 Hz). The mean compensation threshold was 64 Hz (SE: 8 Hz). The significant difference between these thresholds is consistent with the hypothesis that the auditory-vocal feedback system can operate without conscious control and suggests that it may have access to a more sensitive representation of speech formants.
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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 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".