Ears, heads, and eyes: When singers synchronise
Bibliographic record
Abstract
We examined the relationship between endogenous rhythms, auditory and visual cues, and body movement in the temporal coordination of duet singers. Sixteen pairs of experienced vocalists sang a familiar melody in Solo and two Duet conditions. Vocalists sang together in Unison (simultaneously producing identical pitches) and Round Duet conditions (one vocalist, the Follower, producing pitches at an eight-tone delay from their partner, the Leader) while facing Inward (full visual cues) and Outward (reduced visual cues). Larger tempo differences in partners' spontaneous (temporally unconstrained) Solo performances were associated with larger asynchrony in Duet performances, consistent with coupling predictions for oscillators with similar natural frequencies. Vocalists were slightly but consistently more synchronous in Duets when facing their partner (Inward) than when facing Outward; Unison and Round performances were equally synchronous. The greater difficulty of Rounds production was evidenced in vocalists' slower performance rates and more variable head movements; Followers directed their head gaze away from their partner and used bobbing head movements to mark the musical beat. The strength of Followers' head movements corresponded to the amount of tone onset asynchrony with their partners, indicating a strong association between timing and movement under increased attentional and working memory demands in music performance.
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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 | 0.002 |
| 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 | 0.001 |
| 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".