Trumpet Augmentation and Technological Symbiosis
Bibliographic record
Abstract
This article discusses the augmentation of acoustic musical instruments, with a focus on trumpet augmentation. Augmented instruments are acoustic instruments onto which sensors have been mounted in order to provide extra sonic control variables. Trumpets make ideal candidates for augmentation because they have spare physical space on which to mount electronics and spare performer “bandwidth” with which to interact with the augmentations. In this article, underlying concepts of augmented instrument design are discussed along with a review and discussion of twelve existing augmented trumpets and five projects related to mouthpiece augmentation. Common aspects to many of these examples are identified, such as the prevalence of idiosyncratic designs, the use of buttons placed at or near the left-hand playing position, and the focus on measuring or mimicking trumpet valves. Three existing approaches to valve sensing are compared, and a novel method for sensing valve position, based on linear variable differential transformers, is introduced. Based on the review and comparison, we created an example augmented trumpet that tests the feasibility of a modular design paradigm. The results of this review of the state-of-the-art and our own research suggests future directions towards a better understanding of augmented trumpet design.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".