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Record W2405303458

A Paradigm for Physical Interaction with Sound in 3-D Audio Space

2006· article· en· W2405303458 on OpenAlexaff
Mike Wozniewski, Zack Settel, Jeremy R. Cooperstock

Bibliographic record

VenueThe Journal of the Abraham Lincoln Association · 2006
Typearticle
Languageen
FieldComputer Science
TopicMusic Technology and Sound Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsComputer scienceHuman–computer interactionRepresentation (politics)Context (archaeology)Active listeningSound (geography)Virtual realityMusicalMultimediaSpace (punctuation)Sound artAudio signal processingAudio signalDigital signal processingAcousticsCommunication
DOInot available

Abstract

fetched live from OpenAlex

Immersive virtual environments offer the possibility of natural interaction with a virtual scene that is familiar to users because it is based on everyday activity. The use of such environments for the representation and control of interactive musical systems remains largely unexplored. We propose a paradigm for working with sound and music in a physical context, and develop a framework that allows for the creation of spatialized audio scenes. The framework uses structures called soundNodes, soundConnections, and DSP graphs to organize audio scene content, and offers greater control compared to other representations. 3-D simulation with physical modelling is used to define how audio is processed, and can offer users a high degree of expressive interaction with sound, particularly when the rules for sound propagation are bent. Sound sources and sinks are modelled within the scene along with the user/listener/performer, creating a navigable 3-D sonic space for sound-engineering, musical creation, listening and performance.

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)0.001
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 score0.116
Threshold uncertainty score0.171

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.000
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 head0.008
GPT teacher head0.243
Teacher spread0.235 · 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 designTheoretical or conceptual
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

Citations6
Published2006
Admission routes1
Has abstractyes

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