MALSORI (대한음성학회지:말소리)

  • Issue 66
  • /
  • Pages.61-72
  • /
  • 2008
  • /
  • 1226-1173(pISSN)
The Korean Society Of Phonetic Sciences And Speech Technology (대한음성학회)
권호 표지

Performance Improvement of Classification Between Pathological and Normal Voice Using HOS Parameter

HOS 특징 벡터를 이용한 장애 음성 분류 성능의 향상

  • 이지연 (한국정보통신대학교(ICU) 음성/음향 정보 연구실) ;
  • 정상배 (한국정보통신대학교(ICU) 음성/음향 정보 연구실) ;
  • 최흥식 (연세대학교 의과대학 영동세브란스병원 이비인후과) ;
  • 한민수 (한국정보통신대학교(ICU) 음성/음향 정보 연구실)
  • Published : 2008.06.30
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Abstract

This paper proposes a method to improve pathological and normal voice classification performance by combining multiple features such as auditory-based and higher-order features. Their performances are measured by Gaussian mixture models (GMMs) and linear discriminant analysis (LDA). The combination of multiple features proposed by the frame-based LDA method is shown to be an effective method for pathological and normal voice classification, with a 87.0% classification rate. This is a noticeable improvement of 17.72% compared to the MFCC-based GMM algorithm in terms of error reduction.

Keywords