A consort of gestural musical controllers : design, construction, and performance
Bibliographic record
Abstract
This thesis project presents the T-Sticks, a new family of digital musical instruments (DMIs). Most DMIs are either entirely unique interfaces, or exist as design iterations in which each incarnation is intended to improve on the last. The T-Sticks are instead intended to form a complementary group or consort which may be performed ensemble and also performed individually in solo pieces or works for mixed instrumentation. Each of the T-Sticks is based on the same general structure and sensing platform, but each also differs from its siblings in size, weight, timbre and register. This document explores some of the issues challenging and motivating the field of DMI design and performance, and describes the motivations behind the T-Stick project in this context. Several existing DMIs are examined for similarities to the T-Stick and compared in terms of design intention, implementation, and usage. The hardware and software designed and built for this project is presented, along with insights gained through collaboration with performers and composers in the context of McGill University's Digital Orchestra project. The performers in question have collectively practiced and performed with the T-Stick for hundreds of hours in the lab, practice room, and on the concert stage. The consort of T-Sticks will be featured as an ensemble in a piece to be performed during the 2008 MusiMarch festival in Montreal.
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.
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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".