Multilingual Natural Language Processing Approaches for Alzheimer’s Detection: A Scoping Review

ACL ARR 2026 January Submission9849 Authors

06 Jan 2026 (modified: 20 Mar 2026)ACL ARR 2026 January SubmissionEveryoneRevisionsBibTeXCC BY 4.0
Keywords: Alzheimer's ; Multilingual; Speech
Abstract: Spoken language analysis is a compelling tool for detecting signs of Alzheimer’s disease (AD). However, most language-based AD detection resources are only available in English, leaving multilingual or crosslingual AD detection understudied. We review the current state of the field with respect to this topic, compiling recent approaches, constraints, and potential solutions from original work published across engineering, natural language processing, and medical databases from 2004 to the present. From the 776 search results, we identified 42 articles meeting predefined eligibility criteria and summarized their findings. Promising results are reported in almost all studies, but few are integrated into clinical practice. The main limitations of the field are poor standardization, the lack of benchmark data repositories (which in turn hinders direct results comparison), and some disconnect between the study goals and the clinical applications. Active efforts from the research community and industry to close these gaps would support robust integration of research across languages into clinical practice.
Paper Type: Long
Research Area: NLP Applications
Research Area Keywords: Alzheimer's, Dementia detection, speech, language
Contribution Types: Surveys
Languages Studied: English
Submission Number: 9849
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