Sonified Distance in Sensory Substitution Does Not Always Improve Localization: Comparison With a 2-D and 3-D Handheld Device
Bibliographic record
Abstract
Early visual to auditory substitution devices encode 2-D monocular images into sounds while more recent devices use distance information from 3-D sensors. This study assesses whether the addition of sound-encoded distance in recent systems helps to convey the “where” information. This is important to the design of new sensory substitution devices. We conducted experiments for object localization and navigation tasks with a handheld visual to audio substitution system. It comprises 2-D and 3-D modes. Both encode in real-time the position of objects in images captured by a camera. The 3-D mode encodes in addition the distance between the system and the object. Experiments have been conducted with 16 blindfolded sighted participants. For the localization, participants were quicker to understand the scene with the 3-D mode that encodes distances. On the other hand, with the 2-D only mode, they were able to compensate for the lack of distance encoding after a small training. For the navigation, participants were as good with the 2-D only mode than with the 3-D mode encoding distance.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".