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Alzheimers Dement (Amst). 2015 Mar 29;1(1):112-24. doi: 10.1016/j.dadm.2014.11.012. eCollection 2015 Mar.

Automatic speech analysis for the assessment of patients with predementia and Alzheimer's disease.

Author information

1
Research Unit CoBTeK - Cognition Behaviour Technology, Edmond & Lily Safra Research Center, University of Nice Sophia Antipolis, Nice, France; Alzheimer Centre Limburg, Maastricht University Medical Center, School for Mental Health and Neuroscience, Maastricht, The Netherlands.
2
Speech Technologies, IBM Research, Haifa, Israel.
3
Research Unit CoBTeK - Cognition Behaviour Technology, Edmond & Lily Safra Research Center, University of Nice Sophia Antipolis, Nice, France.
4
Alzheimer Centre Limburg, Maastricht University Medical Center, School for Mental Health and Neuroscience, Maastricht, The Netherlands.
5
Research Unit CoBTeK - Cognition Behaviour Technology, Edmond & Lily Safra Research Center, University of Nice Sophia Antipolis, Nice, France; Centre Mémoire de Ressources et de Recherche, CHU de Nice, Nice, France.

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.

KEYWORDS:

Alzheimer's; Assessment; Audio; Dementia; Information and communication technology (ICT); Mild cognitive impairment; Speech analyses; Vocal task

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