Analysis of spontaneous, conversational speech in dementia of Alzheimer type: Evaluation of an objective technique for analysing lexical performance
Abstract
Spontaneous, conversational speech in probable dementia of Alzheimer type (DAT) participants and healthy older controls was analysed using eight linguistic measures. These were evaluated for their usefulness in discriminating between healthy and demented individuals. The measures were; noun rate, pronounrate, verb rate, adjective rate, clause-like semantic unit rate (all per 100 words), including three lexical richness measures; type token ratio (TTR), Brunet's Index (W) and Honore's statistic (R). Results suggest that these measures offer a sensitive method of assessing spontaneous speech output in DAT. Comparison between DAT and healthy older participants demonstrates that these measures discriminate well between these groups. This method shows promise as a diagnostic and prognostic tool, and as a measure for use in clinical trials. Further validation in a large sample of patient versus control ‘norms’ in addition to evaluation in other types of dementia is considered.
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Other reports based on language and speech features ranged from 70% to 89.6% accuracy.
“Other reports based on language and speech features ranged from 70% to 89.6% accuracy.”
From Automatic classification of AD pathology in FTD phenotypes using natural speech (2024) · cites this paper as [17]
Formal thought disorder is most commonly associated with schizophrenia but is often present in other mental illnesses such as mania and depression.
“FTD is most commonly associated with schizophrenia but is often present in other forms of mental illness such as mania, depression, and several others [89], [90].”
From A Review of Automated Speech and Language Features for Assessment of Cognitive and Thought Disorders (2020) · cites this paper as [89]
Multiple studies rely on speech and language as sources of clinical information for Alzheimer's disease.
“Consequently, and due to the ubiquitous nature of speech and language, multiple studies rely on these modalities as sources of clinical information for AD, from foundational qualitative research (e.g., [4, 5]) to more recent work on computational speech technology (e.g., [6–8]).”
From Artificial Intelligence, Speech, and Language Processing Approaches to Monitoring Alzheimer’s Disease: A Systematic Review (2020) · cites this paper as [5]
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References 90 · Cited by 233
- Authors
- Bucks, R. S., Singh, S., Cuerden, J. M., & Wilcock, G. K.
- Affiliations
- Avon and Wiltshire Mental Health Partnership NHS Trust (GB)
- University of Exeter (GB)
- Venue
- Aphasiology
- Publisher
- Informa UK Limited
- Published
- 2000-01
- Volume
- 14
- Issue
- 1
- Pages
- 71-91
- ISSN
- 0268-7038 (ISSN-L)
- 1464-5041
- OpenAlex
- W1994871153
- Cited by
- 233
- References
- 90
- Citations by year
- 2026: 14 · 2025: 13 · 2024: 14 · 2023: 18 · 2022: 16 · 2021: 26 · 2020: 24 · 2019: 20 · 2018: 12 · 2017: 14 · 2016: 13 · 2015: 9 · 2014: 10 · 2013: 2 · 2012: 4
- FWCI
- 0.47
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Aphasiology (publishedVersion)
- ePrints Soton (University of Southampton) (submittedVersion)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neurobiology of Language and Bilingualism
- Social Sciences › Psychology › Developmental and Educational Psychology › Language Development and Disorders
- Keywords
- Alzheimer's disease, dementia, spontaneous speech, conversational speech, linguistic measures, type-token ratio, lexical diversity, speech analysis, diagnostic tools, prognostic tools
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