The relationship between vocal abilities and singing accuracy
Bibliographic record
Abstract
Poor-pitch singing could be caused by poor pitch perception or poor vocal-motor control abilities. This study aims to contrast these two possible causes in order to determine the role of vocal control on the accuracy of sung performances among nonmusicians. Participants matched recordings of their own voices either by singing, or by manipulating those recordings on a physical instrument which could control the pitch of the vocal recording playback by sliding the finger along a position sensor. In addition, participants sang a full song from memory. Overall, participants were more accurate at matching the pitch of the original recording with the instrument than with their voice. In addition, singers who were more accurate at vocal pitch matching tended to have better vocal quality (as assessed through standard measurements, e.g. jitter, stability), and were better at singing whole songs. This pattern of results confirms that vocal-motor control, rather than pitch perception ability, is the primary driver of singing ability, and provides insight into the relationship between pitch accuracy and vocal quality.
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".