Article: On the relevance of using rhythmic metrics and SVM to assess dysarthric severity Journal: International Journal of Biometrics (IJBM) 2014 Vol.6 No.3 pp.248 - 271 Abstract: Studies of dysarthric speech rhythm have explored the possibility of distinguishing healthy speakers from dysarthric ones. These studies also allowed the detection of different types of dysarthria. The present paper aims at assessing the ability of rhythm metrics to perceive dysarthric severity levels. The study reports on the results of a statistical acoustic investigation using various rhythmic metrics. Among these rhythm features, we propose a new rhythm metric based on an approximation of the speakers' rate of articulation. The investigation was carried out on the speech data of US dysarthric patients recorded on the Nemours corpus. The rhythm features are based on two types of segmentation: vocalic/consonantal and voiced/unvoiced interval durations. Results of different classification experiments show that the rhythm-based measures can be used effectively to characterise the dysarthric severity by classifying speakers into their respective categories. Support vector machine classification method has been successfully used to perform the assessment of the dysarthria severity level. Inderscience Publishers - linking academia, business and industry through research

Title: On the relevance of using rhythmic metrics and SVM to assess dysarthric severity

Authors: Habiba Dahmani; Sid-Ahmed Selouani; Noureddine Doghmane; Douglas O'Shaughnessy; Mohamed Chetouani

Addresses: Engineering Sciences Faculty, M'sila University, M'sila, Algeria; Engineering Sciences Faculty, Badji Mokhtar University, Annaba, Algeria; INRS-Telecommunications, Montreal, Quebec, Canada ' Moncton University, Shippagan Campus, 218, boul. J.-D.-Gauthier Shippagan NB, E8S 1P6, Canada ' Engineering Sciences Faculty, Badji Mokhtar University, Annaba, Algeria ' INRS, Montreal, Quebec, Canada ' The Institute of Intelligent Systems and Robotics, Pierre and Marie Curie University, Paris, France

Abstract: Studies of dysarthric speech rhythm have explored the possibility of distinguishing healthy speakers from dysarthric ones. These studies also allowed the detection of different types of dysarthria. The present paper aims at assessing the ability of rhythm metrics to perceive dysarthric severity levels. The study reports on the results of a statistical acoustic investigation using various rhythmic metrics. Among these rhythm features, we propose a new rhythm metric based on an approximation of the speakers' rate of articulation. The investigation was carried out on the speech data of US dysarthric patients recorded on the Nemours corpus. The rhythm features are based on two types of segmentation: vocalic/consonantal and voiced/unvoiced interval durations. Results of different classification experiments show that the rhythm-based measures can be used effectively to characterise the dysarthric severity by classifying speakers into their respective categories. Support vector machine classification method has been successfully used to perform the assessment of the dysarthria severity level.

Keywords: dysarthria; rhythm; pairwise variability index; acoustical analysis; Nemours database; support vector machines; SVM; classification; discriminant analysis; rhythmic metrics; dysarthric severity levels; dysarthric speech rhythms.

DOI: 10.1504/IJBM.2014.064405

International Journal of Biometrics, 2014 Vol.6 No.3, pp.248 - 271

Received: 26 Jun 2013
Accepted: 22 Apr 2014
Published online: 10 Sep 2014 *

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Title: On the relevance of using rhythmic metrics and SVM to assess dysarthric severity

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