Automatic Prosodic Analysis to Identify Mild Dementia.

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. he audio session for each subjec...

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Detalles Bibliográficos
Publicado en:	BioMed Research International Vol. 2015; pp. 1 - 7
Autores principales:	Gonzalez-Moreira, Eduardo, Torres-Boza, Diana, Kairuz, Héctor Arturo, Ferrer, Carlos, Garcia-Zamora, Marlene, Espinoza-Cuadros, Fernando, Hernandez-Gómez, Luis Alfonso
Formato:	pictorial research tables/charts Journal Article
Publicado:	Wiley-Blackwell 10/19/2015
Acceso en línea:	Ver este registro en EBSCOhost

Descripción
Sumario:	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. he 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.