The perceptual and acoustic characteristics of Japanese elderly speech—The relationship between cognition and speech motor performance
Bibliographic record
Abstract
Recent studies showed the evidences that language complexity or cognitive load may deteriorate the speed and accuracy of speech. No study was found to explore the relationship between cognitive load and speech movement directly from the perspective of working memory (WM) capacity. In Reading Span Test (RST), WM capacity would be reduced for speech production as the number of sentences and target words increased. The aim of our study is to reveal perceptual and acoustic characteristics of the elderly speech in relation to WM capacity. It was hypothesized that slower speech rate and/or slurred speech would be observed for elderly adults with reduced WM capacity or low cognitive function. Twelve elderly adult speakers of Japanese participated in this study. The scores of Montreal Cognitive Assessment Japanese version was used to divide the participants into high and low cognitive groups. For RST, each participant was asked to read visually presented sentence(s) aloud and to recall target word(s). Reading performances were recorded by a microphone being set in front of each participant for later acoustic evaluations. The reading performances of two cognitive groups were compared and results regarding on the presence of slower speech rate and slurred speech, judged by experienced speech language pathologists, were presented. We will discuss the relationship between the cognitive load and speech movement in the elderly based on the acoustic evaluation.
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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 | 0.001 | 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".