Evaluation of Speech Amplification Devices in Parkinson's Disease
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to evaluate the efficacy of selected speech amplification devices in individuals with hypophonia and idiopathic Parkinson's disease (PD). METHOD: This study compared the effectiveness of seven devices (ADDvox, BoomVox, ChatterVox, Oticon Amigo, SoniVox, Spokeman, and Voicette) to unamplified speech for 11 participants with PD during conversation in 65-dB SPL multitalker noise, using experience ratings collected from participant questionnaires and speech performance measures (i.e., speech-to-noise ratio [SNR], speech intensity, and intelligibility) obtained from audio recordings. RESULTS: Compared with unamplified speech, device use increased SNR by 1.07-4.73 dB SPL and speech intensity by 1.1-5.1 dB SPL, and it significantly increased transcribed intelligibility from 13.8% to 58.9%. In addition, the type of device used significantly affected speech performance measures (e.g., BoomVox was significantly higher than most of the other devices for SNR, speech intensity, and intelligibility). However, experience ratings did not always correspond to performance measures. CONCLUSIONS: This study found preliminary evidence of improved speech performance with device use for individuals with PD. A tentative hierarchy is suggested for device recommendations. Future research is needed to determine which measures will predict long-term device acceptance in PD.
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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 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".