<i>Live 4 Life</i>: A spatial performance tool to play the ephemeral and improvise with space and playback speeds
Bibliographic record
Abstract
This article describes my own way to improvise with space using a computer-based tool implemented in SuperCollider. The objective of this spatial performance tool is to have an ergonomic spatio-temporal and spectral control over numerous sound objects in real time, in order to alternate between spatialised polyrhythms and textures. After a brief review of spatial audio context, the spatial performance tool is summarised and detailed here by focusing on one of the core parameters: the playback speeds, which can act both on rhythm and space and enable among others the spatio-temporal articulation of the performance. As well as discussing the word ‘comprovisation’ and my conception of human–computer improvisation, the possibilities and approach of the tool in terms of improvisation and controllerism are illustrated through the use and combination of different controllers (computer keyboard, tactile interfaces, force touch sensors). Whereas some controllers are more dedicated to the selection and triggering of streams of spatialised sound events, others have their own mappings and ways of acting on some parameters (depending on the temporality of the sounds: playing or future events).
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 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".