Interaction and the Art of User-Centered Digital Musical Instrument Design
Bibliographic record
Abstract
This thesis documents the formulation of a research-based practice in multimedia art, technology and digital musical instrument design. The primary goal of my research was to investigate the principles and methodologies involved in the structural design of new interactive digital musical instruments aimed at performance by members of the general public, and to identify ways that the design process could be optimized to increase user adoption of these new instruments. The research was performed over three years and moved between studies at the University of Maine, internships in New York, and specialized research at the Input Devices and Music Interaction Laboratory at McGill University. My work is presented in two sections. The first covers early studies in user interaction and exploratory works in web and visual design, sound art, installation, and music performance. While not specifically tied to the research topic of user adoption of digital musical instruments, this work serves as the conceptual and technical background for the dedicated work to follow. The second section is dedicated to focused research on digital musical instrument design through two major projects carried out as a Graduate Research Trainee at McGill University. The first was the design and prototype of the Noisebox, a new digital musical instrument. The purpose of this project was to learn the various stages of instrument design through practical application. A working prototype has been presented and tested, and a second version is currently being built. The second project was a user study that surveyed musicians about digital musical instrument use. It asked questions about background, instrument choice, music styles played, and experiences with and attitudes towards new digital musical instruments. Based on the results of the two research projects, a model of digital musical instrument design is proposed that adopts a user-centered focus, soliciting user input and feedback throughout the design process from conception to final testing. This approach aims to narrow the gap between conceptual design of new instruments and technologies and the actual musicians who would use them.
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How this classification was reachedexpand
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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".