Approaches to Real Time Ambisonic Spatialization and Sound Diffusion using\n Motion Capture
Bibliographic record
Abstract
This paper examines the use of motion capture to control ambisonic spatialization and sound diffusion parameters in real time.The authors use several software programs, developed in Max, to facilitate the gestural control of spatialization.Motion tracking systems using cameras and peripheral devices such as the Leap Motion are explored as viable and expressive means to provide sound localization.This enables the performer to therefore use movement through personal space to control the placement of the sound in a larger performance environment.Three works are discussed, each using a different method: an approach derived from sound diffusion practices, an approach using sonification, and an approach in which the gestures controlling the spatialization are part of the drama of the work.These approaches marry two of the most important research trajectories of the perfor-mance practice of electroacoustic and computer music; the geographical dislocation between the sound source and the actual, perceived sound, and the dislocation of physical causality to the sound.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".