Temporal coordination in joint music performance: effects of endogenous rhythms and auditory feedback
Bibliographic record
Abstract
Many behaviors require that individuals coordinate the timing of their actions with others. The current study investigated the role of two factors in temporal coordination of joint music performance: differences in partners' spontaneous (uncued) rate and auditory feedback generated by oneself and one's partner. Pianists performed melodies independently (in a Solo condition), and with a partner (in a duet condition), either at the same time as a partner (Unison), or at a temporal offset (Round), such that pianists heard their partner produce a serially shifted copy of their own sequence. Access to self-produced auditory information during duet performance was manipulated as well: Performers heard either full auditory feedback (Full), or only feedback from their partner (Other). Larger differences in partners' spontaneous rates of Solo performances were associated with larger asynchronies (less effective synchronization) during duet performance. Auditory feedback also influenced temporal coordination of duet performance: Pianists were more coordinated (smaller tone onset asynchronies and more mutual adaptation) during duet performances when self-generated auditory feedback aligned with partner-generated feedback (Unison) than when it did not (Round). Removal of self-feedback disrupted coordination (larger tone onset asynchronies) during Round performances only. Together, findings suggest that differences in partners' spontaneous rates of Solo performances, as well as differences in self- and partner-generated auditory feedback, influence temporal coordination of joint sensorimotor behaviors.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".