Automated Speech Analysis Applied to Sasang Constitution Classification

음성을 이용한 사상체질 분류 알고리즘

  • 강재환 (한국한의학연구원 체질생물학.의공학연구센터) ;
  • 유종향 (한국한의학연구원 체질의학임상연구센터) ;
  • 이혜정 (한국한의학연구원 체질생물학.의공학연구센터) ;
  • 김종열 (한국한의학연구원 체질생물학.의공학연구센터)
  • Published : 2009.09.30

Abstract

This paper introduces an automatic voice classification system for the diagnosis of individual constitution based on Sasang Constitutional Medicine (SCM) in Traditional Korean Medicine (TKM). For the developing of this algorithm, we used the voices of 473 speakers and extracted a total of 144 speech features from the speech data consisting of five sustained vowels and one sentence. The classification system, based on a rule-based algorithm that is derived from a non parametric statistical method, presents binary negative decisions. In conclusion, 55.7% of the speech data were diagnosed by this system, of which 72.8% were correct negative decisions.

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