Construction and Performance Applications of an Augmented Violin: TRAVIS II
Bibliographic record
Abstract
Abstract We present the second iteration of a Touch-Responsive Augmented Violin Interface System, called TRAVIS II, and two compositions that demonstrate its expressivity. TRAVIS II is an augmented acoustic violin with touch sensors integrated into its 3-D printed fingerboard that track left-hand finger gestures in real time. The fingerboard has four strips of conductive PLA filament that produce an electric signal when fingers press down on each string. Although these sensors are physically robust, they are mechanically assembled and thus easy to replace if damaged. The performer can also trigger presets via four sensors attached to the body of the violin. The instrument is completely wireless, giving the performer the freedom to move throughout the performance space. Although the sensing fingerboard is installed in place of the traditional fingerboard, all other electronics can be removed from the augmented instrument, maintaining the aesthetics of a traditional violin. Our design allows violinists to naturally create music for interactive performance and improvisation without requiring new instrumental techniques. The first author composed two compositions to highlight TRAVIS II: “Dream State” and “Kindred Dichotomy.” Both of these compositions involve improvisation in their creative process and include interactive visuals. In this article we describe the design of the instrument, experiments leading to the sensing fingerboard, performative applications of the instrument, and compositional considerations for the resultant pieces.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".