On the relevance of using rhythmic metrics and SVM to assess dysarthric severity. (1st January 2014)

• Record Type: Journal Article
• Authors: Dahmani, Habiba; Selouani, Sid-Ahmed; Doghmane, Noureddine; O'Shaughnessy, Douglas; Chetouani, Mohamed
• Is Part Of: International journal of biometrics. Volume 6:Number 3(2014)
• Page Start: 248
• Page End: 271
• Publication Date: 2014-01-01
• Subjects: dysarthria -- rhythm -- pairwise variability index -- acoustical analysis -- Nemours database -- support vector machine -- SVM -- classification -- discriminant analysis; Biometric identification -- Periodicals; Biometry -- Periodicals; 570.15195
• Languages: English
• ISSNs: 1755-8301

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.