The Relationship Between Speech Perceptual Discrimination and Speech Production in Parkinson's Disease
Bibliographic record
Abstract
Purpose We recently demonstrated that individuals with Parkinson's disease (PD) respond differentially to specific altered auditory feedback parameters during speech production. Participants with PD respond more robustly to pitch and less robustly to formant manipulations compared to control participants. In this study, we investigated whether differences in perceptual processing may in part underlie these compensatory differences in speech production. Methods Pitch and formant feedback manipulations were presented under 2 conditions: production and listening. In the production condition, 15 participants with PD and 15 age- and gender-matched healthy control participants judged whether their own speech output was manipulated in real time. During the listening task, participants judged whether paired tokens of their previously recorded speech samples were the same or different. Results Under listening, 1st formant manipulation discrimination was significantly reduced for the PD group compared to the control group. There was a trend toward better discrimination of pitch in the PD group, but the group difference was not significant. Under the production condition, the ability of participants with PD to identify pitch manipulations was greater than that of the controls. Conclusion The findings suggest perceptual processing differences associated with acoustic parameters of fundamental frequency and 1st formant perturbations in PD. These findings extend our previous results, indicating that different patterns of compensation to pitch and 1st formant shifts may reflect a combination of sensory and motor mechanisms that are differentially influenced by basal ganglia dysfunction.
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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 | 0.005 |
| 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 | 0.000 | 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".