Drifting pitch awareness after exposure to altered auditory feedback
Bibliographic record
Abstract
Various studies have claimed that the sense of agency is based on a comparison between an internal estimate of an action’s outcome and sensory feedback. With respect to speech, this presumes that speakers have a stable pre-articulatory representation of their own speech. However, recent research suggests that the sense of agency is flexible and thus in some contexts we may feel like we produced speech that was not actually produced by us. The current study tested whether the estimated pitch of one’s articulation (termed ‘pitch awareness’) is affected by manipulated auditory feedback. In four experiments, fifty-six participants produced isolated vowels while being exposed to pitch-shifted auditory feedback. After every vocalization, participants indicated whether they thought the feedback was higher or lower than their actual production. After exposure to a block of high-pitched auditory feedback (+500 cents pitch shift), participants were more likely to label subsequent auditory feedback as “lower than my actual production”, suggesting that prolonged exposure to high-pitched auditory feedback led to a drift in participants’ pitch awareness. The opposite pattern was found after exposure to a constant -500 cents pitch shift. This suggests that pitch awareness is not solely based on a pre-articulatory representation of intended speech or on a sensory prediction, but also on sensory feedback. We propose that this drift in pitch awareness could be indicative of a sense of agency over the pitch-shifted auditory feedback in the exposure block. If so, this suggests that the sense of agency over vocal output is flexible.
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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 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".