• Title/Summary/Keyword: RTF-MVDR

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A Microphone Array Beamforming Algorithm with Inverse Filtering of Relative Transfer Functions in Car Environments (상대전달함수의 역필터링을 이용한 자동차 환경에서의 마이크로폰 어레이 빔형성 기법)

  • Kang Hong-Goo;Hwang Youngsoo;Youn Dae-Hee;Han Chul-Hee
    • The Journal of the Acoustical Society of Korea
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    • v.25 no.1
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    • pp.30-35
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    • 2006
  • In this paper. we Propose a frequency domain beamforming algorithm composed of inverse-filtering stages followed by a MVDR (Minimum-Variance Distortionless Response) beamformer or a GSC (Generalized Sidelobe Canceller). The proposed method is shown to require less complexity than the conventional RTF-MVDR and TF-GSC. respectively, and it is shown that the Proposed method is equivalent to the conventional RTF-MVDR and TF-GSC in optimum solution. In order to evaluate the performance of the Proposed method. speech recognition experiments are performed using the speech database recorded in a car. The Proposed method shows equal or slightly degraded Performance comparing to the conventional methods in terms of the speech recognition rate.

A Microphone Array Beamformer for the Performance Enhancement of Speech Recognizer in Car (차량환경에서 음성인식 성능 향상을 위한 마이크로폰 어레이 빔형성 기법)

  • Han Chul-Hee;Kang Hong-Goo;Hwang Youngsoo;Youn Dae-Hee
    • The Journal of the Acoustical Society of Korea
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    • v.24 no.7
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    • pp.423-430
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    • 2005
  • In this paper. a microphone array beamforming algorithm that reduces the signal distortion caused by reverberation and near-field effect in car environment is proposed. When reverberation or near-field effect is present, an optimum beamformer should be constructed with a steering vector consisting of transfer functions between source and microphones, but it is generally difficult to estimate transfer functions on-line without knowledge of the source signal. Instead, a sub-optimal beamforming algorithm that reduces signal distortion is proposed. It is constructed with steering vectors consisting of relative transfer functions between reference sensor and other sensors. In order to evaluate the performance of the proposed algorithm. we had recorded noisy speech database in a car, and performed speech recognition experiments with HMM Toolkit (HTK) released by Cambridge University. The recognition rate of the proposed algorithm was 15 percents higher than that of the conventional far-field beamformers in best case.