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Record W178275036

SOUNDVIEW: SENSING COLOR IMAGES BY KINESTHETIC AUDIO

2003· article· en· W178275036 on OpenAlexaff
Kees van den Doel

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldNeuroscience
TopicTactile and Sensory Interactions
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsComputer visionArtificial intelligenceComputer scienceColor spaceColor imageComputer graphics (images)Image (mathematics)Image processing
DOInot available

Abstract

fetched live from OpenAlex

An experimental system called SoundView has been devel-oped, which allows the exploration of a color image through touch and hearing. The image is mapped onto a virtual surface with a fine-grained color dependent roughness texture. The user ex-plores the image by moving a pointer device over the image. The pointer acts like a virtual gramophone needle, and the sound pro-duced depends on the motion as well as on the color of the area ex-plored. The roughness texture is obtained by constructing a map-ping of three dimensional color space onto a three dimensional sound space. The mapping tries to achieve maximal alignment of the color and sound spaces by preserving the perceptual metrical and topological structure of color space, as well as by incorporat-ing common associations between sound and color. 1.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.314
Threshold uncertainty score1.000

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)0.0010.001

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 head0.026
GPT teacher head0.275
Teacher spread0.249 · 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.

Study designBench or experimental
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

Citations36
Published2003
Admission routes1
Has abstractyes

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