Pitch perception and production in congenital amusia: Evidence from Cantonese speakers
Bibliographic record
Abstract
This study investigated pitch perception and production in speech and music in individuals with congenital amusia (a disorder of musical pitch processing) who are native speakers of Cantonese, a tone language with a highly complex tonal system. Sixteen Cantonese-speaking congenital amusics and 16 controls performed a set of lexical tone perception, production, singing, and psychophysical pitch threshold tasks. Their tone production accuracy and singing proficiency were subsequently judged by independent listeners, and subjected to acoustic analyses. Relative to controls, amusics showed impaired discrimination of lexical tones in both speech and non-speech conditions. They also received lower ratings for singing proficiency, producing larger pitch interval deviations and making more pitch interval errors compared to controls. Demonstrating higher pitch direction identification thresholds than controls for both speech syllables and piano tones, amusics nevertheless produced native lexical tones with comparable pitch trajectories and intelligibility as controls. Significant correlations were found between pitch threshold and lexical tone perception, music perception and production, but not between lexical tone perception and production for amusics. These findings provide further evidence that congenital amusia is a domain-general language-independent pitch-processing deficit that is associated with severely impaired music perception and production, mildly impaired speech perception, and largely intact speech production.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".