Effects of Multi-talker Noise on the Acoustics of Voiceless Stop Consonants in Parkinson's Disease
Bibliographic record
Abstract
This study examined the effect of increased speech intensity on stop consonant acoustics in Parkinson’s disease (PD). Acoustic analyses focused on measures of spirantization, voicing during closure, stop closure durations, and voice onset time. Ten individuals with Parkinson’s disease and ten age-matched controls were audio recorded while they read aloud words from the Distinctive Features Differences Test (DFD) during two conditions: no noise and 65 dB of multi-talker background noise. When compared to controls, the participants with PD had values that approached a significant difference for the measures related to greater percent voicing into closure (p=0.074), lower mean syllable intensity (p=0.069) and greater spirantization ratio (p=0.094). When compared to the no noise condition, the 65 dB multi-talker noise condition was associated with significant changes in voice onset time (VOT), syllable intensity, spirantization ratio and other measures. In addition, the place of stop consonant production had a significant effect on measures of closure duration, VOT, spectral skewness and other measures. These preliminary findings suggest that additional studies of the effect of changes in speech intensity on stop production in PD are warranted. The results of the present study identified several acoustic measures of stop production that may be useful in future evaluations of treatment outcome in PD.
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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 | 0.000 |
| 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) | 0.000 | 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".