Automatic Assessment of Connected Speech and Its Relation to Memory in Alzheimer’s Disease in Low Education
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Bibliographic record
Abstract
INTRODUCTION: Discourse is one of the main linguistic aspects affected by Alzheimer's disease (AD), and its relationship with memory needs to be further studied, mainly in low education and low socioeconomic status groups. The present study aimed to investigate differences in the recall of short narratives between participants with mild AD and a control group (CG) of typical older adults (CG) with the use of automatic assessment. METHODS: Seventeen older adults diagnosed with AD (mean age 76.41, mean education 5.82) and 34 typical older adults (mean age 74.26, mean education 7.09) were asked to listen to and then retell a short story. Syntactic, lexical, and semantic features were assessed via the NILC-Metrix software, and the features were correlated with episodic, working, and semantic memory assessment. RESULTS: Differences were found in 7 of the 34 features assessed. Syntactically, the group diagnosed with AD produced narratives with fewer sentences, fewer words per sentence, and lower Yngve depth scores. Lexically, the AD group produced narratives with fewer words and prepositions per sentence. Semantically, the narratives produced by the AD group featured words with a lower mean age of acquisition and lower Brunét's index scores. For the CG, episodic memory performance correlated with the ratio of conjunctions. No other significant correlation was found for semantic and working memory in the CG. No correlation was found between memory performance and linguistic features for the AD group. DISCUSSION: The automatic assessment of linguistic features showed impaired narrative recall in participants diagnosed with AD relative to healthy controls at the syntactic, lexical, and semantic levels of discourse. These findings corroborate previous literature showing a decline in discourse production performance resulting from cognitive impairment in AD. CONCLUSION: The assessment of linguistic performance through a narrative recall task provides valuable insights into cognitive decline related to AD.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 it