Creating Non-Visual Non-Verbal Social Interactions in Virtual Reality
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Although virtual reality (VR) was originally conceived of as a multi-sensory experience, most developers of the technology have focused on its visual aspects to the detriment of other senses such as hearing. This paper presents design patterns to make virtual reality fully accessible to non-visual users, including totally blind users, especially with non-verbal social interactions. Non-visual VR has been present in the blindness audio game community since the early 2000s, but the conventions from those interfaces have never been described to a sighted audience, outside of a few limited sonification interface papers. This paper presents non-visual design patterns created by five of the top English-speaking audio game developers through a three round Delphi method, encompassing 29 non-verbal social interactions grouped into 12 categories in VR, including movement, emotes, and self-expression. This paper will be useful to developers of VR experiences who wish to represent non-verbal social information to their users through non-visual conventions. These methods have only been rigorously tested through the commercial market, and not through scientific approaches. These design patterns can serve as the foundation for future investigation in exploring non-visual non-verbal social interactions in VR.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it