POLYPHONIC EMBOUCHURE ON AN INTRICATELY EXPRESSIVE MUSICAL KEYBOARD FORMED BY AN ARRAY OF WATER JETS
Bibliographic record
Abstract
Touching, diverting, restricting, or obstructing water jets constitutes a new type of user-interface for immersive multimedia environments such as totally acoustic, totally electronic, or hybrid musical instruments. The result is a richly expressive input device. In the context of a musical instrument, this device is called a hydraulophone. Developments in the rich expressivity of the hydraulophone are presented, as a new type of embouchure control. This paper presents a new concept called “finger-jet embouchure” in which each “key ” (water jet) on the instrument is governed by fluid-dynamics, rather than by solid key motion. The direct coupling between a musician’s finger and physical sound production in the liquid (which can be detected by underwater microphones and fed into a computer, thus creating a hyperacoustic user-interface) leads to highly expressive performance styles. By designing each note to be associated with one water-jet “mouth ” on the instrument, we give the performer an ability to fluidly interleave the dynamics of many notes simultaneously, producing a phenomenon named “polyphonic embouchure”. The result is the ability to perform richly expressive music, whether on an acoustic hydraulophone, or on an enhanced hydraulophone with sound pickups for hyperacoustic computer performances. 1.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".