Articulatory motor planning and timbral idiosyncrasies as underlying mechanisms of instrument-specific absolute pitch in expert musicians
Bibliographic record
Abstract
The study of musical expertise illustrates how intense training in a specialized domain may instigate development of implicit skills. While absolute pitch, or the ability to identify musical pitches without external reference, is rare even in professional musicians and is understood to have a genetic component, anecdotal evidence and pilot data suggest that some musicians without traditional absolute pitch are nonetheless better able to name notes played on their musical instrument of expertise than notes played on less familiar instruments. We have previously termed this particular gain in absolute pitch identification ability "instrument-specific absolute pitch" (ISAP) and have proposed that this skill is related to learned instrument type-specific timbral and intonational idiosyncrasies and articulatory motor planning activated by the timbre of the instrument. In this Registered Report Protocol, we describe two experiments designed to investigate ISAP in professional oboists. Experiment 1 tests for ISAP ability by comparing oboists' pitch identification accuracies for notes played on the oboe and on the piano. A subset of the participants from Experiment 1 who demonstrate this ability will be recruited for Experiment 2; the purpose of Experiment 2 is to test hypotheses concerning a mechanistic explanation for ISAP. The outcome of these experiments may provide support for the theory that some individuals have ISAP and that the underlying mechanisms of this ability may rely on the perception of subtle timbral/intonational idiosyncrasies and on articulatory motor planning developed through intensive long-term training. In general, this work will contribute to the understanding of specialized expertise, specifically of implicit abilities and biases that are not addressed directly in training, but that may yet develop through practice of a related skill set.
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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 | 0.001 | 0.004 |
| 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 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".