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Record W2007887196 · doi:10.1145/1639642.1639685

Accessible videodescription On-Demand

2009· article· en· W2007887196 on OpenAlexaff
Claude Chapdelaine, Langis Gagnon

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Accessibility for Disabilities
Canadian institutionsComputer Research Institute of Montréal
Fundersnot available
KeywordsUsabilityComputer scienceVisually impairedRendering (computer graphics)MultimediaHuman–computer interactionScreen readerKey (lock)On demandQuality (philosophy)World Wide WebArtificial intelligenceComputer security

Abstract

fetched live from OpenAlex

Providing blind and visually impaired people with the descriptions of key visual elements can greatly improve the accessibility of video, film and television. This project presents a Website platform for rendering videodescription (VD) using an adapted player. Our goal is to test the usability of an accessible player that provides end-users with various levels of VD, on-demand. This paper summarizes the user evaluations covering 1) the usability of the player and its controls, and 2) the quality and quantity of the VD selected. The complete results of these evaluations, including the accessibility of the Website, will be presented in the poster. Final results show that 90% of the participants agreed on the relevancy of a multi-level VD player. All of them rated the player easy to use. Some improvements were also identified. We found that there is a great need to provide blind and visually impaired people with more flexible tool to access rich media content.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.043
Threshold uncertainty score0.144

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0430.006

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 head0.359
Teacher spread0.318 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations13
Published2009
Admission routes1
Has abstractyes

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