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Record W2883414745

Live 4 Life - A spatial performance tool focused on rhythm and parameter loops

2018· article· en· W2883414745 on OpenAlexaff
Christophe Lengelé

Bibliographic record

VenueInternational Computer Music Conference · 2018
Typearticle
Languageen
FieldComputer Science
TopicMusic Technology and Sound Studies
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsSpatializationRendering (computer graphics)Computer scienceLoudspeakerRhythmEvent (particle physics)Artificial intelligenceAcousticsEngineeringElectrical engineering
DOInot available

Abstract

fetched live from OpenAlex

This paper presents a global and integrated spatialization tool that aims to improve and facilitate sound creation process over multiple loudspeakers, from composition to performance. Implemented in SuperCollider, it has a multi-time scale approach, where spatialization is determined both locally on single sound elements and globally on event streams. It seeks to set up a comprehensive library of predefined spatialization models with a dynamic and quick selection among both rendering algorithms and also concrete and abstract spatial composition techniques for an arbitrary, ever-changing number of sources. This programme places emphasis on spatial, rhythmic and other synthesis parameter loops to create polyrhythmic spatializations and aims to question the development of spatio-temporal links between sound objects, their treatments or their reflections in real time.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.808
Threshold uncertainty score0.711

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.034
GPT teacher head0.239
Teacher spread0.205 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2018
Admission routes1
Has abstractyes

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