Change search
ReferencesLink to record
Permanent link

Direct link
Speech Assessment for the Classification of Hypokinetic Dysthria in Parkinson Disease
Dalarna University, School of Technology and Business Studies, Computer Engineering.
2012 (English)Independent thesis Advanced level (degree of Master (Two Years)), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

The aim of this thesis is to investigate computerized voice assessment methods to classify between the normal and Dysarthric speech signals. In this proposed system, computerized assessment methods equipped with signal processing and artificial intelligence techniques have been introduced. The sentences used for the measurement of inter-stress intervals (ISI) were read by each subject. These sentences were computed for comparisons between normal and impaired voice. Band pass filter has been used for the preprocessing of speech samples. Speech segmentation is performed using signal energy and spectral centroid to separate voiced and unvoiced areas in speech signal. Acoustic features are extracted from the LPC model and speech segments from each audio signal to find the anomalies. The speech features which have been assessed for classification are Energy Entropy, Zero crossing rate (ZCR), Spectral-Centroid, Mean Fundamental-Frequency (Meanf0), Jitter (RAP), Jitter (PPQ), and Shimmer (APQ). Naïve Bayes (NB) has been used for speech classification. For speech test-1 and test-2, 72% and 80% accuracies of classification between healthy and impaired speech samples have been achieved respectively using the NB. For speech test-3, 64% correct classification is achieved using the NB. The results direct the possibility of speech impairment classification in PD patients based on the clinical rating scale.

Place, publisher, year, edition, pages
2012. , 49 p.
Keyword [en]
Parkinson’s disease, Hypokinetic dysarthria, Speech segmentation, Levodopa, Acoustic analysis
National Category
Computer Systems
URN: urn:nbn:se:du-10041OAI: diva2:524605
Available from: 2012-05-03 Created: 2012-05-03 Last updated: 2012-05-03Bibliographically approved

Open Access in DiVA

Fulltext(757 kB)3526 downloads
File information
File name FULLTEXT01.pdfFile size 757 kBChecksum SHA-512
Type fulltextMimetype application/pdf

By organisation
Computer Engineering
Computer Systems

Search outside of DiVA

GoogleGoogle Scholar
Total: 3526 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Total: 331 hits
ReferencesLink to record
Permanent link

Direct link