When vocal training masks structure: Individual differences in visual aspects of sung interval size
Bibliographic record
Abstract
Vocal training typically emphasizes aspects of production that are important to pitch and voice quality such as vocal control and breathing. By contrast, visually available aspects of production tend to receive far less attention. Nonetheless, recent research suggests that visual aspects of performance are relevant to audience experience, influencing perception of emotion and structure. With regard to the latter, a linear relation has been demonstrated between the size of sung melodic intervals and the extent of head movement, eyebrow lifting, and mouth opening. Observers track these visually available aspects of song production, and they influence judgments of interval size in a manner that is pre-attentive and automatic. We wondered whether the emphasis on vocal control in classical training might somehow interfere with visual aspects of performance. We asked classically trained and competent amateur vocalists to produce ascending melodic intervals ranging in size from unison to octave. Participants were asked to make estimates of interval size based on observation of visual-only recordings. Accuracy of estimates was higher for intervals that were produced by the untrained group. This provocative finding may have implications for vocal pedagogy.
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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 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".