Assessing Gender Bias in Auditory-Perceptual Ratings of Tracheoesophageal Speakers
Bibliographic record
Abstract
Objective: This study examined the relationship between gender and auditory-perceptual evaluation of tracheoesophageal (TE) speech. Method: We collected auditory-perceptual judgments of two features, speech acceptability and listener comfort, from normal-hearing young adult listeners (n = 16) who were naïve to TE speech. Auditory-perceptual judgments were made for 12 TE speakers (6 men and 6 women) on two occasions separated by between 7 and 14 days. During the first session, listeners were deceived about the gender of the voice samples presented, and in the second session, listeners were informed of the true gender of the voice samples. Results: The findings suggest that a gender bias exists in perceptions of TE speech, and that female TE speakers tend to be disproportionately penalized when compared to their male counterparts when gender is known. Conclusions: These data provide insights into the potential influence of speaker gender on listener judgments of TE speech and the impact that such factors may have on communication. Our data indicate that listeners rate female TE speaker samples as less acceptable and less comfortable to listen to when the samples are known to be female speakers.
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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 | 0.002 | 0.012 |
| 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 | 0.001 |
| Research integrity | 0.000 | 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".