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Development of medical/electrical convergence software for classification between normal and pathological voices

장애 음성 판별을 위한 의료/전자 융복합 소프트웨어 개발

  • Moon, Ji-Hye (Department of Biomedical Engineering, Jungwon University) ;
  • Lee, JiYeoun (Department of Biomedical Engineering, Jungwon University)
  • 문지혜 (중원대학교 의료공학과) ;
  • 이지연 (중원대학교 의료공학과)
  • Received : 2015.10.30
  • Accepted : 2015.12.20
  • Published : 2015.12.28

Abstract

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.

Keywords

Higher-order Statistics;Acoustical analysis;Convergence voice analysis software;Biomedical electricity

Acknowledgement

Supported by : 한국연구재단

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