Direct magnitude estimation and interval scaling of pleasantness and severity in dysphonic and normal speakers
Bibliographic record
Abstract
The purpose of this study was to determine the validity of voice pleasantness and overall voice severity ratings of dysphonic and normal speakers using direct magnitude estimation (DME) and equal-appearing interval (EAI) auditory-perceptual scaling procedures. Twelve naive listeners perceptually evaluated voice pleasantness and severity from connected speech samples produced by 24 adult dysphonic speakers and 6 normal adult speakers. A statistical comparison of the two auditory-perceptual scales yielded a linear relationship representative of a metathetic continuum for voice pleasantness. A statistical relationship that is consistent with a prothetic continuum was revealed for ratings of voice severity. These data provide support for the use of either DME or EAI scales when making auditory-perceptual judgments of pleasantness, but only DME scales when judging overall voice severity for dysphonic speakers. These results suggest further psychophysical study of perceptual dimensions of voice and speech must be undertaken in order to avoid the inappropriate and invalid use of EAI scales used in the auditory-perceptual evaluation of the normal and dysphonic voice.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".