Journal of the Institute of Electronics Engineers of Korea SP (대한전자공학회논문지SP)

The Institute of Electronics and Information Engineers (대한전자공학회)
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Speech Enhancement based on Minima Controlled Recursive Averaging Technique Incorporating Second-order Conditional Maximum a posteriori Criterion

2차 조건 사후 최대 확률 기반 최소값 제어 재귀평균기법을 이용한 음성향상

  • Kum, Jong-Mo (Department of Electronics Engineering, Inha University) ;
  • Chang, Joon-Hyuk (Department of Electronics Engineering, Inha University)
  • 금종모 (인하대학교 전자공학부) ;
  • 장준혁 (인하대학교 전자공학부)
  • Published : 2009.07.25
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Abstract

In this paper, we propose a novel approach to improve the performance of minima controlled recursive averaging (MCRA) which is based on the second-order conditional maximum a posteriori (CMAP). From an investigation of the MCRA scheme, it is discovered that the MCRA method cannot take full consideration of the inter-frame correlation of voice activity since the noise power estimate is adjusted by the speech presence probability depending on an observation of the current frame. To avoid this phenomenon, the proposed MCRA approach incorporates the second-order CMAP criterion in which the noise power estimate is obtained using the speech presence probability conditioned on both the current observation and the speech activity decisions in the previous two frames. Experimental results show that the proposed MCRA technique based on second-order conditional MAP yields better results compared to the conventional MCRA method.

본 논문에서는 기존의 Minima Controlled Recursive Averaging (MCRA)에 2차 조건 사후 최대 확률기법을 적용한 음성 향상 기법을 제안한다. 기존의 MCRA 방법은 현제 프레임의 음성 신호 존재 확률로 잡음 추정을 조정하기 때문에 음성 활동의 프레임간의 상호 연관성을 배제 하였다. 본 논문에서 제안한 알고리즘은 직전 2 프레임에서의 음성의 존재와 부재에 대한 조건을 부여해 주어 현제 프레임의 음성 신호 존재 확률을 수정하는 음성향상 기법을 적용한다. 제안된 2차 조건 사후 최대 확률기법을 적용한 MCRA 방법이 기존의 MCRA 방법보다 향상된 음성향상 결과를 나타내었다.

Keywords

References

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