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International Journal of Speech Technology
Erschienen in: International Journal of Speech Technology 2/2017

04.03.2017

Detecting multiple system atrophy, Parkinson and other neurological disorders using voice analysis

verfasst von: Achraf Benba, Abdelilah Jilbab, Ahmed Hammouch

Erschienen in: International Journal of Speech Technology | Ausgabe 2/2017

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Abstract

In this study, we wanted to discriminate between three groups of patients. Each group contains nine voice recordings collected from nine patients. The three groups are: Patients who suffer From Multiple system atrophy, patients who suffer from Parkinson’s disease and patients who suffer from other neurological disorders. We extracted from each voice sample from 1 to 20 cepstral coefficients of the MFCC, PLP and RASTA-PLP. We used for classification Support Vector Machines with its different kernels. The results were very encouraging and they varied between 92.59 and 100% of accuracy.
Vorheriger Artikel TAMEEM V1.0: speakers and text independent Arabic automatic continuous speech recognizer
Nächster Artikel Extraction of terms and semantic relationships from Arabic texts for automatic construction of an ontology

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Metadaten
Titel
Detecting multiple system atrophy, Parkinson and other neurological disorders using voice analysis
verfasst von
Achraf Benba
Abdelilah Jilbab
Ahmed Hammouch
Publikationsdatum
04.03.2017
Verlag
Springer US
Erschienen in
International Journal of Speech Technology / Ausgabe 2/2017
Print ISSN: 1381-2416
Elektronische ISSN: 1572-8110
DOI
https://doi.org/10.1007/s10772-017-9404-6

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