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...
| Publicado en: | BioMed Research International Vol. 2015; pp. 1 - 7 |
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| Autores principales: | , , , , , , |
| Formato: | pictorial research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
10/19/2015
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=128652130&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 128652130 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 10/19/2015 vid: 2015 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 128652130 128652130 128652130 10.1155/2015/916356 128652130 ppf: 1 ppct: 6 formats: fmt: @attributes: type: P tig: atl: Automatic Prosodic Analysis to Identify Mild Dementia. aug: au: Gonzalez-Moreira, Eduardo Torres-Boza, Diana Kairuz, Héctor Arturo Ferrer, Carlos Garcia-Zamora, Marlene Espinoza-Cuadros, Fernando Hernandez-Gómez, Luis Alfonso affil: Center for Studies on Electronics and Information Technologies, Universidad Central "Marta Abreu" de Las Villas, 54830 Santa Clara, Cuba sug: subj: Dementia Diagnosis Speech Task Performance and Analysis Autoanalysis Human Exploratory Research Audiorecording Reading Validity ab: 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. pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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