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Quantitative assessment of syllabic timing deficits in ataxic dysarthria
conference contribution
posted on 2018-01-01, 00:00 authored by Bipasha KashyapBipasha Kashyap, Pubudu PathiranaPubudu Pathirana, Malcolm Horne, Laura Power, David SzmulewiczParametric analysis of Cerebellar Dysarthria (CD)
may be valuable and more informative compared to its clinical
assessment. A quantifiable estimation of the timing deficits in
repeated syllabic utterance is described in the current study.
Thirty-five individuals were diagnosed with cerebellar ataxia to
varying degrees and twenty-six age-matched healthy controls
were recruited. To automatically detect the local maxima of each
syllable in the recorded speech files, a topographic prominence
incorporated concept is designed. Subsequently, four acoustic
features and eight corresponding parametric measurements are
extracted to identify articulatory deficits in ataxic dysarthria.
A comparative study on the behaviour of these measures for
dysarthric and non-dysarthric subjects is presented in this
paper. The results are further explored using a dimension-reduction
tool (Principal Component Analysis) to emphasize
variation and bring out the strongest discriminating patterns in
our feature dataset.
may be valuable and more informative compared to its clinical
assessment. A quantifiable estimation of the timing deficits in
repeated syllabic utterance is described in the current study.
Thirty-five individuals were diagnosed with cerebellar ataxia to
varying degrees and twenty-six age-matched healthy controls
were recruited. To automatically detect the local maxima of each
syllable in the recorded speech files, a topographic prominence
incorporated concept is designed. Subsequently, four acoustic
features and eight corresponding parametric measurements are
extracted to identify articulatory deficits in ataxic dysarthria.
A comparative study on the behaviour of these measures for
dysarthric and non-dysarthric subjects is presented in this
paper. The results are further explored using a dimension-reduction
tool (Principal Component Analysis) to emphasize
variation and bring out the strongest discriminating patterns in
our feature dataset.
History
Event
IEEE Engineering in Medicine and Biology Society. Conference (40th : 2018 : Honolulu, Hawaii)Series
IEEE Engineering in Medicine and Biology Society ConferencePagination
425 - 428Publisher
Institute of Electrical and Electronics EngineersLocation
Honolulu, HawaiiPlace of publication
Piscataway, N.J.Publisher DOI
Start date
2018-07-18End date
2018-07-21ISSN
1557-170XeISSN
1558-4615ISBN-13
9781538636466Language
engPublication classification
E Conference publication; E1 Full written paper - refereedCopyright notice
2018, IEEEEditor/Contributor(s)
[Unknown]Title of proceedings
EMBC 2018 : Proceedings of the 40th IEEE Engineering in Medicine and Biology Society Annual International ConferenceUsage metrics
Keywords
Cerebellar Dysarthria (CD)Parametric analysisclinical assessmentrepeated syllabic utterancetiming deficitscerebellar ataxiaScience & TechnologyTechnologyEngineering, BiomedicalEngineering, Electrical & ElectronicEngineeringdysarthriaspeech disorderrepeated syllabletopographic prominenceSPEECHMechanical Engineering
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