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Development of medical/electrical convergence software for classification between normal and pathological voices
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  • Journal title : Journal of Digital Convergence
  • Volume 13, Issue 12,  2015, pp.187-192
  • Publisher : The Society of Digital Policy and Management
  • DOI : 10.14400/JDC.2015.13.12.187
 Title & Authors
Development of medical/electrical convergence software for classification between normal and pathological voices
Moon, Ji-Hye; Lee, JiYeoun;
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If the software is developed to analyze the speech disorder, the application of various converged areas will be very high. This paper implements the user-friendly program based on CART(Classification and regression trees) analysis to distinguish between normal and pathological voices utilizing combination of the acoustical and HOS(Higher-order statistics) parameters. It means convergence between medical information and signal processing. Then the acoustical parameters are Jitter(%) and Shimmer(%). The proposed HOS parameters are means and variances of skewness(MOS and VOS) and kurtosis(MOK and VOK). Database consist of 53 normal and 173 pathological voices distributed by Kay Elemetrics. When the acoustical and proposed parameters together are used to generate the decision tree, the average accuracy is 83.11%. Finally, we developed a program with more user-friendly interface and frameworks.
Higher-order Statistics;Acoustical analysis;Convergence voice analysis software;Biomedical electricity;
 Cited by
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