Helping Persons with Cognitive Disabilities using Voice-Activated Personal Assistants
Bibliographic record
Abstract
The objective of this study was to determine whether Canadians with cognitive disabilities such as autism could benefit from voice-activated intelligent personal assistants to access digital services and increase their participation in the digital economy. We recruited 24 participants aged 18 to 64 with a cognitive disability to serve as advisors in this study. They were each given an Amazon Echo Dot free of charge to use in their home environments for a month and then interviewed to determine their likes, dislikes, intentions, and whatever new ideas they had for improving the Echo Dot applications. Video recordings of interviews with advisors and/or caregivers were collected for offline analysis. We found that the advisors were overwhelmingly positive about using the Dot for variety of information-retrieval tasks ranging from asking for weather reports to satisfying more serious information needs such as answering health-related questions and planning public transportation routes. Both Advisors and their caregivers found that alarms, reminders and Alexa “routines” were particularly helpful features. Alexa skills available in French are not as numerous or varied as those in English and bilingual advisors often interacted with Alexa in English more than in French.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".