title: Automatic Prosodic Analysis to Identify Mild Dementia.
abstract: This paper describes an exploratory technique to identify mild dementia by assessing the degree of speech deficits. A total of twenty participants were used for this experiment, ten patients with a diagnosis of mild dementia and ten participants like healthy control. The audio session for each subject was recorded following a methodology developed for the present study. Prosodic features in patients with mild dementia and healthy elderly controls were measured using automatic prosodic analysis on a reading task. A novel method was carried out to gather twelve prosodic features over speech samples. The best classification rate achieved was of 85% accuracy using four prosodic features. The results attained show that the proposed computational speech analysis offers a viable alternative for automatic identification of dementia features in elderly adults.
authors.affiliation: Center for Studies on Electronics and Information Technologies, Universidad Central "Marta Abreu" de Las Villas, 54830 Santa Clara, Cuba.
authors.forename: Eduardo
authors.initials: E
authors.lastname: Gonzalez-Moreira
authors.affiliation: Center for Studies on Electronics and Information Technologies, Universidad Central "Marta Abreu" de Las Villas, 54830 Santa Clara, Cuba.
authors.forename: Diana
authors.initials: D
authors.lastname: Torres-Boza
authors.affiliation: Center for Studies on Electronics and Information Technologies, Universidad Central "Marta Abreu" de Las Villas, 54830 Santa Clara, Cuba.
authors.forename: Héctor Arturo
authors.initials: HA
authors.lastname: Kairuz
authors.affiliation: Center for Studies on Electronics and Information Technologies, Universidad Central "Marta Abreu" de Las Villas, 54830 Santa Clara, Cuba.
authors.forename: Carlos
authors.initials: C
authors.lastname: Ferrer
authors.affiliation: Center for Elderly Adults No. 2, 54830 Santa Clara, Cuba.
authors.forename: Marlene
authors.initials: M
authors.lastname: Garcia-Zamora
authors.affiliation: Signal, Systems and Radiocommunications Department, Universidad Politécnica de Madrid, 28040 Madrid, Spain.
authors.forename: Fernando
authors.initials: F
authors.lastname: Espinoza-Cuadros
authors.affiliation: Signal, Systems and Radiocommunications Department, Universidad Politécnica de Madrid, 28040 Madrid, Spain.
authors.forename: Luis Alfonso
authors.initials: LA
authors.lastname: Hernandez-Gómez
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D016022:Case-Control Studies; D003704:Dementia / Q000175:diagnosis* / Q000503:physiopathology; D005260:Female; D006801:Humans; D008297:Male; D012815:Signal Processing, Computer-Assisted; D013018:Sound Spectrography; D013060:Speech / Q000145:classification*; D013061:Speech Acoustics; D060388:Support Vector Machine