Bibliographic record
Abstract
In this paper, we present BrailleSketch, a gesture-based text input method on touchscreen smartphones for people with visual impairments. To input a letter with BrailleSketch, a user simply sketches a gesture that passes through all dots in the corresponding Braille code for that letter. BrailleSketch allows users to place their fingers anywhere on the screen to begin a gesture and draw the Braille code in many ways. To encourage users to type faster, BrailleSketch does not provide immediate letter-level audio feedback but instead provides word-level audio feedback. It uses an auto-correction algorithm to correct typing errors. Our evaluation of the method with ten participants with visual impairments who each completed five typing sessions shows that BrailleSketch supports a text entry speed of 14.53 word per min (wpm) with 10.6% error. Moreover, our data suggest that the speed had not begun to plateau yet by the last typing session and can continue to improve. Our evaluation also demonstrates the positive effect of the reduced audio feedback and the auto-correction algorithm.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".