Cross-domain correlation in pitch perception, the influence of native language
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The current study explores how language experience may shape the correlation between lexical tone and musical pitch perception. A two domains (music and lexical tone) by two languages (tone, Mandarin Chinese and non-tone, Dutch) design is adopted. Participants were tested on their discrimination of Mandarin Chinese lexical tones, Montreal Battery of Evaluation of Amusia (MBEA), and Musical Ear Test (MET). The Chinese listeners outperformed the Dutch listeners on both MBEA and MET, but had comparable accuracies for the lexical tone discrimination. Importantly, a significant cross-domain correlation was only observed for the Dutch listeners but not for the Chinese listeners. For tone language listeners, once lexical tones have been acquired, native listeners perceive them as phonological categories, and split them from other pitch variations that do not play a phonemic role. Non-tone language listeners, on the other hand, perceive both lexical tones and musical pitch on a psycho-acoustical basis, hence exhibit a unified perception of pitch across the two domains.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it