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Record W2244497244 · doi:10.1109/iisa.2015.7388078

Interactive rate acoustical occlusion/diffraction modeling for 2D virtual environments & games

2015· article· en· W2244497244 on OpenAlexaff
Brent Cowan, Bill Kapralos

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicMusic Technology and Sound Studies
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsDiffractionComputer scienceTask (project management)ObstacleAcousticsBendingHuman–computer interactionComputer graphics (images)Computer visionArtificial intelligenceEngineeringOpticsPhysics

Abstract

fetched live from OpenAlex

Despite the importance of acoustical diffraction (the "bending" of sound around an obstacle) in the real-world, diffraction in virtual environments and game worlds is often overlooked. Part of this stems from the fact that modeling occlusion/diffraction effects is a difficult and computationally intensive task. Inspired by our previous work that saw the development of a three-dimensional acoustical occlusion method, here we present a method that approximates acoustical occlusion/diffraction effects for dynamic and interactive two-dimensional virtual environments and games (or three-dimensional environments that can be approximated by a two-dimensional mapping). We also discuss an innovative use for the method allowing it to be incorporated into the artificial intelligence of non-player characters (e.g., enemies), allowing them to "perceive" sounds and therefore behave in a more natural, and realistic manner. Preliminary experimental results demonstrate that the method is capable of operating at interactive rates.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.874
Threshold uncertainty score0.388

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 head0.041
GPT teacher head0.287
Teacher spread0.245 · 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 designSimulation or modeling
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
Published2015
Admission routes1
Has abstractyes

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