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Record W3132574854 · doi:10.1145/3430524.3440635

Playing by Ear: Designing for the Physical in a Sound-Based Virtual Reality Narrative

2021· article· en· W3132574854 on OpenAlexafffund
Daniel Harley, Aneesh P. Tarun, Bonnie J. Stinson, Tudor Tibu, Ali Mazalek

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsToronto Metropolitan UniversityUniversity of Waterloo
FundersOntario Ministry of Research and InnovationSocial Sciences and Humanities Research Council of CanadaCanada Research Chairs
KeywordsNarrativeEmbodied cognitionGRASPVirtual realityFocus (optics)Human–computer interactionSound (geography)Computer scienceSound designDanceAestheticsVisual artsAcousticsArtArtificial intelligence

Abstract

fetched live from OpenAlex

We present two proof-of-concept narrative VR experiences with a focus on sound-based physical interactions. Responding to a call to expand upon current design conceptualizations, we draw on tangible sound-based design in order to develop considerations for the body and physical environments within VR narratives. We propose that a focus on the actions the player is asked to perform (e.g., touch, stand, kneel, grasp, walk, listen, reach, dance) can contribute to an understanding of VR as a sensory, embodied medium that offers ways to playfully engage with physical reality rather than simulate it entirely.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.854
Threshold uncertainty score0.299

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 science0.0000.000
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 head0.045
GPT teacher head0.328
Teacher spread0.283 · 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

Citations3
Published2021
Admission routes2
Has abstractyes

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