Individual differences in the perception of melodic contours and pitch-accent timing in speech: Support for domain-generality of pitch processing.
Bibliographic record
Abstract
Do the same mechanisms underlie processing of music and language? Recent investigations of this question have yielded inconsistent results. Likely factors contributing to discrepant findings are use of small samples and failure to control for individual differences in cognitive ability. We investigated the relationship between music and speech prosody processing, while controlling for cognitive ability. Participants (n = 179) completed a battery of cognitive ability tests, the Montreal Battery of Evaluation of Amusia (MBEA) to assess music perception, and a prosody test of pitch peak timing discrimination (early, as in insight vs. late, incite). Structural equation modeling revealed that only music perception was a significant predictor of prosody test performance. Music perception accounted for 34.5% of variance on prosody test performance; cognitive abilities and music training added only about 8%. These results indicate musical pitch and temporal processing are highly predictive of pitch discrimination in speech processing, even after controlling for other possible predictors of this aspect of language processing.
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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 | 0.001 | 0.000 |
| 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) | 0.000 | 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".