Real-time measurement/viewing of vocal-tract influence during wind instrument performance
Bibliographic record
Abstract
Since the early 1980s, there have been a number of investigations into the role and influence of a player’s vocal tract on the sound production of wind instruments. While the underlying acoustic principles are relatively well understood, a general lack of agreement remains within both the music acoustics and performance communities with regard to the importance of this mechanism during playing conditions. Disparities arise in part because subtle manipulations of the oral cavity can affect the response of the instrument without necessarily producing effects audible to an observer. A real-time measurement system is demonstrated that provides a visual comparison of the relative strengths of the ‘‘upstream’’ windway and ‘‘downstream’’ air column impedances under playing conditions. The system assumes continuity of volume flow on either side of the ‘‘reed,’’ which leads to a direct proportionality between the upstream and downstream pressures and impedances. Playing experiments clearly demonstrate many instances in which vocal-tract manipulations can cause impedance peak magnitudes in the mouth cavity to exceed those in the downstream air column. In addition to providing visual ‘‘proof’’ of such manipulations, the system is expected to offer a pedagogical tool to help performers better learn how to make use of this control mechanism.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".