Automatic speech analysis for the assessment of patients with predementia and Alzheimer's disease
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
No Canadian affiliation. An affiliation-only frame — the usual design — would never have seen this work. It is one of the works that make the case for inverting the frame.
Machine scores (provisional)
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
- Teacher spread
- 0.298 · how far apart the two teachers sit on this one work
- Validation status
score_only:v0-immature-baseline· verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it
Abstract
BACKGROUND: To evaluate the interest of using automatic speech analyses for the assessment of mild cognitive impairment (MCI) and early-stage Alzheimer's disease (AD). METHODS: Healthy elderly control (HC) subjects and patients with MCI or AD were recorded while performing several short cognitive vocal tasks. The voice recordings were processed, and the first vocal markers were extracted using speech signal processing techniques. Second, the vocal markers were tested to assess their "power" to distinguish among HC, MCI, and AD. The second step included training automatic classifiers for detecting MCI and AD, using machine learning methods and testing the detection accuracy. RESULTS: The classification accuracy of automatic audio analyses were as follows: between HCs and those with MCI, 79% ± 5%; between HCs and those with AD, 87% ± 3%; and between those with MCI and those with AD, 80% ± 5%, demonstrating its assessment utility. CONCLUSION: Automatic speech analyses could be an additional objective assessment tool for elderly with cognitive decline.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
The record
- Venue
- Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring
- Topic
- Voice and Speech Disorders
- Field
- Medicine
- Canadian institutions
- —
- Funders
- Canadian Institute of Ukranian Studies, University of AlbertaUniversité Nice Sophia Antipolis
- Keywords
- AudiologyCognitive impairmentCognitionAlzheimer's diseaseDiseaseMedicineCognitive declineSpeech recognitionPsychologyDementiaComputer scienceInternal medicineNeuroscience
- Has abstract in OpenAlex
- yes