Speech Intensity Response to Altered Intensity Feedback in Individuals With Parkinson's Disease
Bibliographic record
Abstract
Purpose Hypophonia (low speech intensity) is the most common speech symptom experienced by individuals with Parkinson's disease (IWPD). Previous research suggests that, in IWPD, there may be abnormal integration of sensory information for motor production of speech intensity. In the current study, intensity of auditory feedback was systematically manipulated (altered in both positive and negative directions) during sensorimotor conditions that are known to modulate speech intensity in everyday contexts in order to better understand the role of auditory feedback for speech intensity regulation. Method Twenty-six IWPD and 24 neurologically healthy controls were asked to complete the following tasks: converse with the experimenter, start vowel production, and read sentences at a comfortable loudness, while hearing their own speech intensity randomly altered. Altered intensity feedback conditions included 5-, 10-, and 15-dB reductions and increases in the feedback intensity. Speech tasks were completed in no noise and in background noise. Results IWPD displayed a reduced response to the altered intensity feedback compared to control participants. This reduced response was most apparent when participants were speaking in background noise. Specific task-based differences in responses were observed such that the reduced response by IWPD was most pronounced during the conversation task. Conclusions The current study suggests that IWPD have abnormal processing of auditory information for speech intensity regulation, and this disruption particularly impacts their ability to regulate speech intensity in the context of speech tasks with clear communicative goals (i.e., conversational speech) and speaking in background noise.
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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 | 0.000 | 0.002 |
| 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".