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Speech Analysis by Natural Language Processing Techniques: A Possible Tool for Very Early Detection of Cognitive Decline?
Beltrami D, Gagliardi G, Rossini Favretti R, Ghidoni E, Tamburini F, Calzà L.. Frontiers in aging neuroscience, 2018-11-13
Topic: Risk, prevention and care in population studies
Neuropsychological tests showed significant differences between controls and mdMCI, and between controls and eD participants; GPCog, MoCA, PF, and SF also discriminated between controls and aMCI. In the linguistic experiments, a number of features regarding lexical, acoustic and syntactic aspects were significant in differentiating between mdMCI, eD, and CG (non-parametric statistical analysis). Some features, mainly in the acoustic domain also discriminated between CG and aMCI. Linguistic features of spontaneous speech transcribed and analyzed by NLP techniques show significant differences between controls and pathological states (not only eD but also MCI) and seems to be a promising approach for the identification of preclinical stages of dementia. Long duration follow-up studies are needed to confirm this assumption.
Key findings
- Neuropsychological tests showed significant differences between controls and mdMCI, and between controls and eD participants; GPCog, MoCA, PF, and SF also discriminated between controls and aMCI.
- In the linguistic experiments, a number of features regarding lexical, acoustic and syntactic aspects were significant in differentiating between mdMCI, eD, and CG (non-parametric statistical analysis).
- Some features, mainly in the acoustic domain also discriminated between CG and aMCI.
- Linguistic features of spontaneous speech transcribed and analyzed by NLP techniques show significant differences between controls and pathological states (not only eD but also MCI) and seems to be a promising approach for the identification of preclinical stages of dementia.
- Long duration follow-up studies are needed to confirm this assumption.
Why it matters
This study found that computer analysis of speech features could distinguish people with mild cognitive impairment or early dementia from controls. The authors say longer follow-up studies are needed before this can be confirmed as a way to detect very early decline.
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Study details
- Participants96
- Evidence strengthLow
How this study scored 52/100
Published in a peer-reviewed journal. Scored zero for study design, effect reported and randomised / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Frontiers in aging neuroscience) |
| Journal's citation record | 2 / 4 | Frontiers in Aging Neuroscience: journal h-index 174 (OpenAlex, 2026-10-29) |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 2 / 5 | 2018 — within 10 year(s) of the newest study here |
| Sample size | 1 / 4 | 96 participants |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 3 / 3 | Studied in people (participant count stated) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 5 / 7 | Cited 174 times (OpenAlex, 2026-10-10) |
| Citations per year | 3 / 5 | 17.4 citations a year over 10 year(s) since 2018 |
| Impact for its field and year | 4 / 6 | Cited 8.3× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 2 / 6 | Cited by 4 other studies in this library |
| Still being cited | 3 / 4 | Cited 75 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 3 / 4 | Last-listed author Laura Calzà: h-index 53 (OpenAlex, whole career) |
| Institution's track record | 1 / 3 | University of Bologna: institution h-index 989 (OpenAlex) |
| Multi-centre collaboration | 1 / 3 | OpenAlex lists 2 institution(s) in 1 country |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 30483116) |
| Free to read | 2 / 2 | Free to read |
| Total | 52 / 100 | — |
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Read the original
- DOI: 10.3389/fnagi.2018.00369
- PubMed: 30483116
- Original source →
- Free full text: Frontiers in Aging Neuroscience →
Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. Check the citation against the original before you use it.
APA 7th
Beltrami, D., Gagliardi, G., Rossini Favretti, R., Ghidoni, E., Tamburini, F., & Calzà, L. (2018). Speech Analysis by Natural Language Processing Techniques: A Possible Tool for Very Early Detection of Cognitive Decline? Frontiers in aging neuroscience. https://doi.org/10.3389/fnagi.2018.00369
Vancouver
Beltrami D, Gagliardi G, Rossini Favretti R, Ghidoni E, Tamburini F, Calzà L. Speech Analysis by Natural Language Processing Techniques: A Possible Tool for Very Early Detection of Cognitive Decline? Frontiers in aging neuroscience. 2018. doi:10.3389/fnagi.2018.00369. PMID: 30483116.
BibTeX
@article{beltrami2018-30483116,
author = {Beltrami, D. and Gagliardi, G. and Rossini Favretti, R. and Ghidoni, E. and Tamburini, F. and Calzà, L.},
title = {{Speech Analysis by Natural Language Processing Techniques: A Possible Tool for Very Early Detection of Cognitive Decline?}},
journal = {Frontiers in aging neuroscience},
year = {2018},
doi = {10.3389/fnagi.2018.00369},
pmid = {30483116},
url = {https://doi.org/10.3389/fnagi.2018.00369}
}
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