The Audibility of Low Vision Devices with Speech Output Used by Older Adults with Dual Sensory Impairment
Bibliographic record
Abstract
SIGNIFICANCE: The successful uptake, integration, and use of vision rehabilitation devices with speech output depend to a large part on their audibility. However, individuals with combined vision and hearing impairments are at a disadvantage when using devices that do not consider multiple impairments. PURPOSE: Sensory rehabilitation for individuals with combined vision and hearing impairment often relies on the use of assistive technology devices that use speech outputs (e.g., talking clock), but in individuals with dual impairment, their use is likely compromised by a concurrent hearing loss. The goal of this study was to evaluate the audibility of these devices in a population of individuals with acquired dual sensory impairment. METHODS: We measured the ability to correctly repeat speech output presented by three assistive technology devices (talking watch, calculator, scanner) and confidence levels in response accuracy in 24 participants with visual impairment only and in 22 individuals with dual sensory loss. Stimuli were presented at three volumes that were repeated one or four times. Participants were placed at a fixed distance of 74 cm from the sound source. RESULTS: The pattern of results was similar across the different devices, whereby an interaction of volume and repetition indicated that participants' accuracy to repeat a phrase and their confidence in their response improved with increasing volume, but more so at higher numbers of repetition (P < .05; ω, from 0.005 to 0.298). Participants with dual sensory loss generally had lower accuracy and confidence. CONCLUSIONS: Scores and confidence levels being very low across devices and users suggest that even participants with normal hearing for their age experienced a certain level of difficulty understanding speech output, confirming the need for better assistive technology device design.
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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 | 0.001 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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 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".