피치 반감 배가를 유발하는 병적인 음성 분석을 위한 강인한 피치 검출 알고리즘

Robust Pitch Detection Algorithm for Pathological Voice inducing Pitch Halving and Doubling

  • 장승진 (연세대학교, 보건과학대학 의공학과) ;
  • 최성희 (위스콘신대학 이비인후/두경부 전문외과) ;
  • 김효민 (연세대학교, 보건과학대학 의공학과) ;
  • 최홍식 (연세대학교 의학대학 이비인후과) ;
  • 윤영로 (연세대학교, 보건과학대학 의공학과)
  • Jang, Seung-Jin (Dept. of biomedical engineering, College of Health & Science, Yonsei University) ;
  • Choi, Seong-Hee (Div. of Otolaryngology-Head and Neck Surgery, Dept. of Surgery, University of Wisconsin-Maidison) ;
  • Kim, Hyo-Min (Dept. of biomedical engineering, College of Health & Science, Yonsei University) ;
  • Choi, Hong-Shik (Dept. of Otolaryngology, College of Medicine, Yonsei University) ;
  • Yoon, Young-Ro (Dept. of biomedical engineering, College of Health & Science, Yonsei University)
  • 발행 : 2007.07.18

초록

In field of voice pathology, diverse statistics extracted form pitch estimation were commonly used to assess voice quality. In this study, we proposed robust pitch detection algorithm which can estimate pitch of pathological voices in benign vocal fold lesions. we also compared our proposed algorithm with three established pitch detection algorithms; autocorrelation, simplified inverse filtering technique, and nonlinear state-space embedding methods. In the database of total pathological voices of 99 and normal voices of 30, an analysis of errors related with pitch detection was evaluated between pathological and normal voices, or among the types of pathological voices. According to the results of pitch errors, gross pitch error showed some increases in cases of pathological voices; especially excessive increase in PDA based on nonlinear time-series. In an analysis of types of pathological voices classified by aperiodicity and the degree of chaos, the more voice has aperiodic and chaotic, the more growth of pitch errors increased. Consequently, it is required to survey the severity of tested voice in order to obtain accurate pitch estimates.

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