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Why Alzheimer's Speech Screening Fails to Generalize: Bridging the Deployment Gap via Cross-Corpus Evidence Anchoring

Paper recorded by Signals 4 on 2026-09-25 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-25 on arXiv · recorded by Signals 4 on 2026-09-28

Category: cs.CL · 自然语言处理 · first seen 2026-09-28

Abstract

Speech-based screening is a promising, non-invasive approach for detecting Alzheimer's disease and related cognitive risks. However, models trained on a single domain often generalize poorly to unseen languages, tasks, or recording protocols. This paper investigates this deployment gap using a leave-one-corpus-out evaluation across four distinct datasets. Among 70 interpretable speech and language

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#13 most recent of 267 cs.CL papers we have recorded · ↑ newer: The Right Information Extraction Pipeline Depends on the Document: Acc · ↓ older: Identifying Scientists on X
Cite this page: Why Alzheimer's Speech Screening Fails to Generalize: Bridging the Deployment Gap via Cross-Corpus Evidence Anchoring: the #13 most recent of 267 cs.CL papers we have recorded (as of 2026-09-25). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/why-alzheimer-s-speech-screening-fails-to-generalize-bridging-the-deployment-gap.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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