Journal of the Korea Institute of Information and Communication Engineering (한국정보통신학회논문지)

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
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Voice Activity Detection in Noisy Environment based on Statistical Nonlinear Dimension Reduction Techniques

통계적 비선형 차원축소기법에 기반한 잡음 환경에서의 음성구간검출

  • 한학용 (동명정보대학교 정보공학부) ;
  • 이광석 (진주산업대학교 전자공학과) ;
  • 고시영 (경일대학교 전자정보공학부) ;
  • 허강인 (동아대학교 전자공학과)
  • Published : 2005.08.01
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Abstract

This Paper proposes the likelihood-based nonlinear dimension reduction method of the speech feature parameters in order to construct the voice activity detecter adaptable in noisy environment. The proposed method uses the nonlinear values of the Gaussian probability density function with the new parameters for the speec/nonspeech class. We adapted Likelihood Ratio Test to find speech part and compared its performance with that of Linear Discriminant Analysis technique. In experiments we found that the proposed method has the similar results to that of Gaussian Mixture Models.

본 논문은 잡음 환경하에서 적응 가능한 음성구간검출를 구축하기 위하여 우도기반의 음성 특징 파라미터의 비선형 차원축소 방법을 제안한다. 제안하는 차원축소 방법은 음성/비음성 클래스에 대한 가우시아 확률 밀도 함수의 비선형적 우도값을 새로운 특징으로 취하는 방법이다. 음성구간검출기의 음성/비음성 결정은 우도비 검증(LRT)의 통계적 방법을 이용하며, 선형판별분석(LDA)에 의한 차원축소 결과와 성능을 비교한다. 실험 결과 제안된 차원 축소 방법으로 음성 특징 파라미터를 2차원으로 축소한 결과가 원래 특징백터의 차원에서의 결과와 대등한 성능을 확인하였다.

Keywords

References

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