Perception of speaker sex in re-synthesized children's voices
Bibliographic record
Abstract
Recent studies have shown that fundamental frequency (F0) and average formant frequencies (FF) provide important cues for the perception of speaker sex. Experiments on vocoded adult voices have indicated that upward scaling of F0 and FFs increases the probability that a voice will be perceived as female while downward scaling increases the probability that the voice will be perceived as male. The present study extends these manipulations to children’s voices. Separate groups of adult listeners heard vocoded /hVd/ syllables spoken by five boys and five girls from 14 age groups (5–18 years) in four synthesis conditions using the STRAIGHT vocoder. These conditions involved swapping F0 and/or FFs to the opposite-sex average within each age group. Compared to the synthesized, unswapped originals, both the F0-swapped condition and the FF-swapped condition resulted in lower sex recognition accuracy for the older females but relatively smaller effects for males. The combined F0 + FF swapped condition produced the largest drop in performance for both sexes, consistent with findings indicating that a change in F0 or FFs alone is generally insufficient to produce a compelling conversion of speaker sex in adults. [Hillenbrand and Clark, Attention Percep. Psychophys. 71(5), 1150–1166 (2009).]
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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 | 0.002 |
| 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) | 0.002 | 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".