Modeling the perception of speaker age and sex in children's voices
Bibliographic record
Abstract
At previous meetings, we presented data on the perception of speaker sex and age in children's voices. The stimuli common to these experiments were /hVd/ syllables in isolation and sentence context. Here we present the results of a modeling study in which acoustic measurements of the /hVd/ syllables were used to predict listener judgments of age and sex. Variables were selected based on preliminary analyses and suggestions from the literature: (1) duration; (2) average fundamental frequency; (3) geometric mean of F1 F2 F3; (4) magnitude difference between harmonics 1 and 2; (5) magnitude difference between harmonic 1 and F3 peak; (6) Cepstral pitch prominence; (7) Harmonic-to-noise ratio. Logistic regression models were constructed to predict listeners' judgments of speaker sex, and mixed effects linear regression models for speaker age. Results confirmed the importance of F0, formant frequencies and measures related to the voicing source for both age and sex. Regression coefficients for judgments of age and sex were similar to those for veridical age and sex when regressed on the same physical measures, suggesting a near-optimal use of cues by listeners.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".