• 제목/요약/키워드: Permutation Ambiguities

검색결과 2건 처리시간 0.017초

시간-주파수 마스킹과 고차 신호 통계를 이용한 음향 반향신호 제거 (Acoustic Echo Cancellation using Time-Frequency Masking and Higher-order Statistics)

  • 김경재;남상원
    • 전기학회논문지
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    • 제56권3호
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    • pp.629-631
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    • 2007
  • In hands-free full-duplex communication systems, acoustic signals picked up by the microphones can be mixed with echo signals as well as noises, which may result in poor performance of the corresponding communication system. Also, the system performance may decrease further if the reverberation occurs since it is harder to estimate the impulse response of the demixing system. For blind source separation (BSS) in such cases, a time-frequency masking approach can be employed to separate undesired echo signals and noises, but, permutation ambiguities also should be solved for the echo cancellation. In this paper, we propose a new acoustic echo cancellation (AEC) approach utilizing the time-frequency masking and higher-order statistics, whereby a desired signal selection, based on coherence and third-order statistics (i.e., kurtosis), is introduced along with output signal normalization. Simulation results demonstrate that the proposed approach yields better echo and noise cancellation performances than the conventional AEC approaches.

잡음 상황에서 DUET 블라인드 신호 분리 알고리즘과 스케일 계수 추정을 이용한 음향 반향신호 제거 (Acoustic Echo Cancellation using the DUET Algorithm and Scaling Factor Estimation)

  • 김경재;서재범;남상원
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2006년 학술대회 논문집 정보 및 제어부문
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    • pp.416-418
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    • 2006
  • In this paper, a new acoustic echo cancellation approach based on the DUET algorithm and scaling factor estimation is proposed to solve the scaling ambiguity in case of blind separation based acoustic echo cancellation in a noisy environment. In hands-free full-duplex communication system. acoustic noises picked up by the microphone are mixed with echo signal. For this reason, the echo cancellation system may provide poor performance. For that purpose, a degenerate unmixing estimation technique, adjusted in the time-frequency domain, is employed to separate undesired echo signals and noises. Also, since scaling and permutation ambiguities have not been solved in the blind source separation algorithm, kurtosis for the desired signal selection and a scaling factor estimation algorithm are utilized in this rarer for the separation of an echo signal. Simulation results demonstrate that the proposed approach yields better echo cancellation and noise reduction performances, compared with conventional methods.

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