Matching fundamental and formant frequencies in vowels
Bibliographic record
Abstract
In natural speech, there is a moderate correlation between fundamental frequency (F0) and formant frequencies (FF) associated with differences in larynx and vocal tract size across talkers. This study asks whether listeners prefer combinations of mean F0 and mean FF that mirror the covariation of these properties. The stimuli were vowel triplets (/i/-/a/-/u/) spoken by two men and two women and subsequently processed by Kawahara’s STRAIGHT vocoder. Experiment 1 included two continua, each containing 25 vowel triplets: one with the spectrum envelope (FF) scale factor fixed at 1.0 (i.e., unmodified) and F0 varied over ±2 oct, the other with F0 scale factor fixed at 1.0 and FF scale factors between 0.63 and 1.58. Listeners used a method of adjustment procedure to find the ‘‘best voice’’ in each set. For each continuum, best matches followed a unimodal distribution centered on the mean F0 or mean FF (F1, F2, F3) observed in measurements of vowels spoken by adult males and females. Experiment 2 showed comparable results when male vowels were scaled to the female range and vice versa. Overall the results suggest that listeners have an implicit awareness of the natural covariation of F0 and FF in human voices.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".