Home trials of a speech synthesizer in severe dysarthria: Patterns of use, satisfaction and utility of word prediction
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to evaluate a speech synthesizer with respect to patterns of use and satisfaction, during a 2-month trial at home, and the usefulness of the word prediction function. DESIGN: Prospective study. PARTICIPANTS: Of the 24 patients with severe dysarthria recruited, 10 completed the study. Five patients had cerebral palsy, 3 amyotrophic lateral sclerosis, one locked-in syndrome, and one anoxic brain damage. Mean age was 32 (standard deviation 21) years (range 9-66 years). METHODS: Each participant received 10 hours of training with the device (Dialo) and then used it at home for 2 months. The main outcome measures were: level of use recorded by the device, Quebec User Evaluation of Satisfaction with Assistive Technology (QUEST) satisfaction score (maximum = 5), and time needed to take dictations of standard-dictionary and personal-dictionary words with and without word prediction. RESULTS: Level of use varied widely across participants. Overall satisfaction at the end of the home trial was high, with a mean QUEST score of 3.4 (SD 1) and was related to the level of use of the device. Level of satisfaction at the end of the training session could not predict the level of use at home. No significant differences were found in dictation-taking times with and without word prediction. However, 6 of the 10 patients took dictation faster with than without word prediction. CONCLUSION: This study provides the first evidence supporting the benefits of a speech synthesizer used at home for several weeks. Word prediction is useful for some patients even if increase in dictation speed did not reach significance.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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".