Investigating the perception of relative speaker size using synthetic talkers
Bibliographic record
Abstract
Several previous experiments have investigated the perception of speaker size by presenting listeners with acoustic stimuli that differ in average f0 and/or apparent vocal tract length (i.e., higher formant frequencies overall), and asking listeners to make judgments of relative or absolute speaker size. Typically, these experiments use stimuli with a fixed phonetic content so that the acoustic characteristics of the stimuli may be compared directly. In this experiment, listeners were presented with pairs of vowels produced by synthetic speakers with different apparent vocal tract lengths and the same f0, and were asked to make judgments of relative size. However, listeners were presented with either the same, or different vowels produced by the two speakers. In some cases, differences associated with varying vocal tract lengths were in conflict with differences arising from the formant patterns associated with the differing vowel categories (e.g., lower F1 and F2 for /u/ vs /e/). Results suggest that judgments of relative size are affected by both the vowel categories presented and the apparent vocal tract lengths of the synthetic speakers. That is, more than a simple (category-corrected) vocal tract length estimate is involved in making size judgments for an unknown speaker.
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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 | 0.006 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".