Formant frequencies, vowel identity, and the perceived relative tallness of synthetic speakers
Bibliographic record
Abstract
Listeners can make consistent judgments regarding the tallness of speakers [Rendall etal., J. Exp. Psych: Human Percep. Perform. 33, 1208 (2007)]. These judgments are informed by the f0 and formant frequencies (FFs) of a speaker's voice. However, FFs are also cues to vowel identity, such that a small speaker producing an /u/ might have lower average FFs than a larger speaker producing an /æ/. Do listeners use absolute FFs to judge speaker tallness, or do they “correct” for phonetic identity and consider the FFs of a vowel relative to those expected for that category? To test this, a series of synthetic vowels (/i æ u/) with different FF scalings and different numbers of formants (2–5) were created. These scalings were intended to replicate speakers of different vocal tract lengths (i.e., sizes). Participants were presented with pairs of vowels and asked to indicate which vowel sounded like it had been produced by a taller speaker. Results indicate that listeners consider both absolute and phonetically “corrected” FF information and that formants higher than F3 greatly reduce listener's reliance on absolute F1 and F2 information in making speaker size judgments.
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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 | 0.000 | 0.005 |
| 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 | 0.001 | 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".