Trumpet Augmentation and Technological Symbiosis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it