A tonal-language benefit for pitch in normally-hearing and cochlear-implanted children
Bibliographic record
Abstract
In tonal languages, voice pitch inflections change the meaning of words, such that the brain processes pitch not merely as an acoustic characterization of sound but as semantic information. In normally-hearing (NH) adults, this linguistic pressure on pitch appears to sharpen its neural encoding and can lead to perceptual benefits, depending on the task relevance, potentially generalizing outside of the speech domain. In children, however, linguistic systems are still malleable, meaning that their encoding of voice pitch information might not receive as much neural specialization but might generalize more easily to ecologically irrelevant pitch contours. This would seem particularly true for early-deafened children wearing a cochlear implant (CI), who must exhibit great adaptability to unfamiliar sounds as their sense of pitch is severely degraded. Here, we provide the first demonstration of a tonal language benefit in dynamic pitch sensitivity among NH children (using both a sweep discrimination and labelling task) which extends partially to children with CI (i.e., in the labelling task only). Strong age effects suggest that sensitivity to pitch contours reaches adult-like levels early in tonal language speakers (possibly before 6 years of age) but continues to develop in non-tonal language speakers well into the teenage years. Overall, we conclude that language-dependent neuroplasticity can enhance behavioral sensitivity to dynamic pitch, even in extreme cases of auditory degradation, but it is most easily observable early in life.
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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".