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Record W2010218626 · doi:10.1017/s1355771809000284

Instrumental Listening: sonic gesture as design principle

2009· article· en· W2010218626 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueOrganised Sound · 2009
Typearticle
Languageen
FieldComputer Science
TopicMusic Technology and Sound Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsGestureComputer scienceActive listeningPerceptionA priori and a posterioriControl (management)Point (geometry)Human–computer interactionArtificial intelligenceCommunicationPsychologyMathematicsEpistemology

Abstract

fetched live from OpenAlex

In the majority of discussions surrounding the design of digital instruments and real-time performance systems, notions such as control and mapping are seen from a classical systems point of view: the former is often seen as a variable from an input device or perhaps some driving signal, while the latter is considered as the liaison between input and output parameters. At the same time there is a large body of research regarding gesture in performance that is concerned with the expressive and communicative nature of musical performance. While these views are certainly central to a conceptual understanding of ‘instrument’, it can be limiting to consider them a priori as the only proper model, and to mediate one’s conception of digital instrument design by fixed notions of control, mapping and gesture. As an example of an alternative way to view instrumental response, control structuring and mapping design, this paper discusses the concept of gesture from the point of view of the perception of human intentionality in sound and how one might consider this in interaction design.

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.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.326
Threshold uncertainty score0.659

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 science0.0010.000
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 head0.016
GPT teacher head0.252
Teacher spread0.237 · 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