ArticleAlzheimer's research & therapy2021
Correlating natural language processing and automated speech analysis with clinician assessment to quantify speech-language changes in mild cognitive impairment and Alzheimer's dementia.
Article in Alzheimer's research & therapy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers, 1 of them a synthesis that pooled it.
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Who cites it
45 citing papers in PubMed, 1 synthesis or guideline pooled it, 84 citations in OpenAlex.
- Speech changes in old age: Methodological considerations for speech-based discrimination of healthy ageing and Alzheimer's disease.International journal of language & communication disordersPooled it
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- An End-to-End Overview of Clinical Speech AI.IEEE transactions on audio, speech, and language processing (2025) · 2026Article
- Speech and language outcome measures in clinical trials of Alzheimer's and Parkinson's diseases.Expert review of neurotherapeutics · 2026Review
- How culture shapes subjective cognitive decline reporting: Refining assessment tools with digital solutions.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Linguistic Markers in Spontaneous Speech: Insights into Subjective Cognitive Decline (Review).Healthcare (Basel, Switzerland) · 2025Review
- Urban mental health: a position paper of the European psychiatric association.European psychiatry : the journal of the Association of European Psychiatrists · 2025Review
- Facets of language performance in early-onset and late-onset Alzheimer's disease dementia.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
- Clinical applications of large language models in medicine and surgery: A scoping review.The Journal of international medical research · 2025Article
- Facets of language performance in early-onset and late-onset Alzheimer's disease dementia.medRxiv : the preprint server for health sciences · 2025Article
- A Systematic Review of Natural Language Processing Techniques for Early Detection of Cognitive Impairment.Mayo Clinic proceedings. Digital health · 2025Review
- Rethinking the diagnosis of primary progressive aphasia: current challenges and future directions.Frontiers in aging neuroscience · 2025Article
- Findings from a social media listening study on Chinese patients with Alzheimer's disease: a content analysis.General psychiatry · 2025Article
- Artificial Intelligence and Medical Education (2013-2024): A Scopus-Based Bibliometric Analysis.The East African health research journal · 2025Article
- The Potential of Automated Assessment of Cognitive Function Using Non-Neuroimaging Data: A Systematic Review.Journal of clinical medicine · 2024Review
- Remote Digital Technologies for the Early Detection and Monitoring of Cognitive Decline in Patients With Type 2 Diabetes: Insights From Studies of Neurodegenerative Diseases.Journal of diabetes science and technology · 2024Review
- Storyteller in ADNI4: Application of an early Alzheimer's disease screening tool using brief, remote, and speech-based testing.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Article
- Automated Speech Analysis in Bipolar Disorder: The CALIBER Study Protocol and Preliminary Results.Journal of clinical medicine · 2024Article
- Distinguishable features of spontaneous speech in Alzheimer's clinical syndrome and healthy controls.Neuropsychology, development, and cognition. Section B, Aging, neuropsychology and cognition · 2024Article
Corrections and comments
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Authors and funding
11 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundLanguage impairment is an important marker of neurodegenerative disorders. Despite this, there is no universal system of terminology used to describe these impairments and large inter-rater variability can exist between clinicians assessing language. The use of natural language processing (NLP) and automated speech analysis (ASA) is emerging as a novel and potentially more objective method to assess language in individuals with mild cognitive impairment (MCI) and Alzheimer's dementia (AD). No studies have analyzed how variables extracted through NLP and ASA might also be correlated to language impairments identified by a clinician.
methodsAudio recordings (n=30) from participants with AD, MCI, and controls were rated by clinicians for word-finding difficulty, incoherence, perseveration, and errors in speech. Speech recordings were also transcribed, and linguistic and acoustic variables were extracted through NLP and ASA. Correlations between clinician-rated speech characteristics and the variables were compared using Spearman's correlation. Exploratory factor analysis was applied to find common factors between variables for each speech characteristic.
resultsClinician agreement was high in three of the four speech characteristics: word-finding difficulty (ICC = 0.92, p<0.001), incoherence (ICC = 0.91, p<0.001), and perseveration (ICC = 0.88, p<0.001). Word-finding difficulty and incoherence were useful constructs at distinguishing MCI and AD from controls, while perseveration and speech errors were less relevant. Word-finding difficulty as a construct was explained by three factors, including number and duration of pauses, word duration, and syntactic complexity. Incoherence was explained by two factors, including increased average word duration, use of past tense, and changes in age of acquisition, and more negative valence.
conclusionsVariables extracted through automated acoustic and linguistic analysis of MCI and AD speech were significantly correlated with clinician ratings of speech and language characteristics. Our results suggest that correlating NLP and ASA with clinician observations is an objective and novel approach to measuring speech and language changes in neurodegenerative disorders.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.