title: Automatic speech analysis for the assessment of patients with predementia and Alzheimer's disease.
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.
  
  
  CONCLUSIONS
  Automatic speech analyses could be an additional objective assessment tool for elderly with cognitive decline.
authors.affiliation: 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.
authors.forename: Alexandra
authors.initials: A
authors.lastname: König
authors.affiliation: Speech Technologies, IBM Research, Haifa, Israel.
authors.forename: Aharon
authors.initials: A
authors.lastname: Satt
authors.affiliation: Speech Technologies, IBM Research, Haifa, Israel.
authors.forename: Alexander
authors.initials: A
authors.lastname: Sorin
authors.affiliation: Speech Technologies, IBM Research, Haifa, Israel.
authors.forename: Ron
authors.initials: R
authors.lastname: Hoory
authors.affiliation: Speech Technologies, IBM Research, Haifa, Israel.
authors.forename: Orith
authors.initials: O
authors.lastname: Toledo-Ronen
authors.affiliation: Research Unit CoBTeK - Cognition Behaviour Technology, Edmond & Lily Safra Research Center, University of Nice Sophia Antipolis, Nice, France.
authors.forename: Alexandre
authors.initials: A
authors.lastname: Derreumaux
authors.affiliation: Research Unit CoBTeK - Cognition Behaviour Technology, Edmond & Lily Safra Research Center, University of Nice Sophia Antipolis, Nice, France.
authors.forename: Valeria
authors.initials: V
authors.lastname: Manera
authors.affiliation: Alzheimer Centre Limburg, Maastricht University Medical Center, School for Mental Health and Neuroscience, Maastricht, The Netherlands.
authors.forename: Frans
authors.initials: F
authors.lastname: Verhey
authors.affiliation: Alzheimer Centre Limburg, Maastricht University Medical Center, School for Mental Health and Neuroscience, Maastricht, The Netherlands.
authors.forename: Pauline
authors.initials: P
authors.lastname: Aalten
authors.affiliation: 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.
authors.forename: Phillipe H
authors.initials: PH
authors.lastname: Robert
authors.affiliation: 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.
authors.forename: Renaud
authors.initials: R
authors.lastname: David
keywords: Alzheimer's; Assessment; Audio; Dementia; Information and communication technology (ICT); Mild cognitive impairment; Speech analyses; Vocal task