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Quantitative assessment of speech in cerebellar ataxia using magnitude and phase based cepstrum
journal contribution
posted on 2020-04-01, 00:00 authored by Bipasha KashyapBipasha Kashyap, Pubudu PathiranaPubudu Pathirana, M Horne, L Power, D SzmulewiczThe clinical assessment of speech abnormalities in Cerebellar Ataxia (CA) is time-consuming and inconsistent. We have developed an automated objective system to quantify CA severity and thereby facilitate remote monitoring and optimisation of therapeutic interventions. A quantitative acoustic assessment could prove to be a viable biomarker for this purpose. Our study explores the use of phase-based cepstral features extracted from the modified group delay function as a complement to the features obtained from the magnitude cepstrum. We selected a combination of 15 acoustic measurements using RELIEF feature selection algorithm during the feature optimisation process. These features were used to segregate ataxic speakers from normal speakers (controls) and objectively assess them based on their severity. The effectiveness of our study has been experimentally evaluated through a clinical study involving 42 patients diagnosed with CA and 23 age-matched controls. A radial basis function kernel based support vector machine (SVM) classifier achieved a classification accuracy of 84.6% in CA–Control discrimination [area under the ROC curve (AUC) of 0.97] and 74% in the modified 3-level CA severity estimation (AUC of 0.90) deduced from the clinical ratings. The strong classification ability of selected features and the SVM model supports this scheme’s suitability for monitoring CA related speech motor abnormalities.
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Journal
Annals of biomedical engineeringVolume
48Issue
4Pagination
1322 - 1336Publisher
SpringerLocation
New York, N.Y.Publisher DOI
ISSN
0090-6964eISSN
1573-9686Language
engPublication classification
C Journal article; C1 Refereed article in a scholarly journalUsage metrics
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