The Journal of the Acoustical Society of Korea (한국음향학회지)

The Acoustical Society of Korea (한국음향학회)
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Speech Enhancement Based on Mixture Hidden Filter Model (HFM) Under Nonstationary Noise

혼합 은닉필터모델 (HFM)을 이용한 비정상 잡음에 오염된 음성신호의 향상

  • 강상기 (서울대학교 대학원 전기·컴퓨터공학부) ;
  • 백성준 (전남대학교 전자컴퓨터정보통신공학부) ;
  • 이기용 (숭실대학교 정보통신과) ;
  • 성굉모 (서울대학교 전기·컴퓨터공학부)
  • Published : 2002.05.01
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Abstract

The enhancement technique of noise signal using mixture HFM (Midden Filter Model) are proposed. Given the parameters of the clean signal and noise, noisy signal is modeled by a linear state-space model with Markov switching parameters. Estimation of state vector is required for estimating original signal. The estimation procedure is based on mixture interacting multiple model (MIMM) and the estimator of speech is given by the weighted sum of parallel Kalman filters operating interactively. Simulation results showed that the proposed method offers performance gains relative to the previous results with slightly increased complexity.

비정상 잡음에 오염된 음성신호의 향상을 위하여 혼합 은닉필터모델 (HFM: Hidden Filter Model)에 기초한 기법을 제안하였다. 오염된 음성신호를 선형상태방정식으로 모델링하고 파라미터는 마코프 모델에 따른다고 가정하였다. 이 파라미터들은 잡음에 오염되지 않은 학습신호로부터 추정할 수 있다. 추정과정은 혼합 상호복합모델 (IMM: Interacting Multiple Model)에 기초하여 이루어지며, 음성신호의 추정값은 상호작용하는 병렬의 칼만 필터들의 가중합으로 주어진다. 실험결과로부터 제안한 방법의 성능이 기존의 방법에 비해 개선되었음을 확인할 수 있었다.

Keywords

References

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