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Blind Noise Separation Method of Convolutive Mixed Signals

컨볼루션 혼합신호의 암묵 잡음분리방법

  • Lee, Haeng-Woo (Dept. of Intelligent Information Communication, Namseoul University)
  • 이행우 (남서울대학교 지능정보통신공학과)
  • Received : 2022.05.27
  • Accepted : 2022.06.17
  • Published : 2022.06.30

Abstract

This paper relates to the blind noise separation method of time-delayed convolutive mixed signals. Since the mixed model of acoustic signals in a closed space is multi-channel, a convolutive blind signal separation method is applied and time-delayed data samples of the two microphone input signals is used. For signal separation, the mixing coefficient is calculated using an inverse model rather than directly calculating the separation coefficient, and the coefficient update is performed by repeated calculations based on secondary statistical properties to estimate the speech signal. Many simulations were performed to verify the performance of the proposed blind signal separation. As a result of the simulation, noise separation using this method operates safely regardless of convolutive mixing, and PESQ is improved by 0.3 points compared to the general adaptive FIR filter structure.

본 논문은 시간지연 컨볼루션 혼합신호의 암묵잡음분리방법에 관한 것이다. 폐쇄된 공간에서 음향신호의 혼합모델은 다채널이기 때문에 convolutive 암묵신호분리방법을 적용하며 두 마이크 입력신호의 시간지연된 데이터 샘플들을 사용한다. 이 신호분리방법은 분리계수를 직접 계산하는 것이 아니라 역방향 모델을 이용하여 혼합계수를 산출하며, 계수의 갱신이 2차 통계적 성질에 기반한 반복적인 계산에 의해 이루어진다. 제안한 암묵신호분리의 성능을 검증하기 위해 많은 시뮬레이션을 수행하였다. 모의실험 결과, 이 방법을 사용한 잡음분리는 컨볼루션혼합에 상관없이 안전하게 동작하고, 일반적인 적응 FIR(Finite Impulse Response) 필터구조에 비해 PESQ(Perceptual Evaluation of Speech Quality)가 0.3점 개선되는 것으로 나타났다.

Keywords

Acknowledgement

이 논문은 2022년도 남서울대학교 학술연구비 지원에 의해 연구되었음.

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