Bibliographic record
Abstract
Individuals already have awareness of their voice at infancy [Dondi et al., 1999, DevPsych 418], and demonstrate own-voice egotism later in life [Hughes & Harrison, 2013, Percept 941-949], but dissatisfaction with hearing their voice recorded [Holzman & Rousey, 1966, JPersonSoc 79] suggests possible misjudgment of own-voice characterisitics. A strong bone-conduction hypothesis [e.g. Tonndorf, 1976, AudSys 37-84] suggests that live-spoken voices are heard as if through a low-pass filter, so that one’s own recorded voice should sound comparatively higher in pitch. Studies have challenged the notion that air-conduction differences completely account for this perceptual contrast [e.g. Maurer & Landis, 1990, FolPhonLogo 226-229]. However, previous methodology does not fully account for own-voice egotism, and the complex influence of social expectations remains uncertain. We test gender-based pitch expectations as one potential social factor against the strong bone-conduction hypothesis [Peng et al., 2021, AusJPsych 71]. Based on the own-voice egotism literature, we predict that pitch perception will contradict a strong bone-conduction hypothesis, with female-identifying participants believing their recorded voice is lowered, and male-identifying participants believing theirs is raised. Participants record a neutral statement before leaving the room for 10 minutes. Upon returning, participants are told their recording may have been pitch-altered. After hearing the unaltered recording, participants rate its authenticity and how they would adjust the pitch to sound like themselves. While results show no significant effect for gender, most participants believe their recorded voices have been lowered in pitch, counter to a strong bone-conduction hypothesis. This suggests that individuals do not judge own-voice characteristics accurately, that factors beyond air conduction differences and gender contribute to this misjudgment, and that there is more complexity than previously believed regarding own-voice pitch perception in recordings. Implications and directions for future work will be discussed.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.711 | 0.526 |
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".