Intelligibility benefit for familiar voices is not accompanied by better discrimination of fundamental frequency or vocal tract length
Bibliographic record
Abstract
Speech is more intelligible when it is spoken by familiar than unfamiliar people. If this benefit arises because key voice characteristics like perceptual correlates of fundamental frequency or vocal tract length (VTL) are more accurately represented for familiar voices, listeners may be able to discriminate smaller manipulations to such characteristics for familiar than unfamiliar voices. We measured participants' (N = 17) thresholds for discriminating pitch (correlate of fundamental frequency, or glottal pulse rate) and formant spacing (correlate of VTL; 'VTL-timbre') for voices that were familiar (participants' friends) and unfamiliar (other participants' friends). As expected, familiar voices were more intelligible. However, discrimination thresholds were no smaller for the same familiar voices. The size of the intelligibility benefit for a familiar over an unfamiliar voice did not relate to the difference in discrimination thresholds for the same voices. Also, the familiar-voice intelligibility benefit was just as large following perceptible manipulations to pitch and VTL-timbre. These results are more consistent with cognitive accounts of speech perception than traditional accounts that predict better discrimination.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".