A Novel Covariance Matrix Estimation Method for MVDR Beamforming In Audio-Visual Communication Systems

Gyeong-Kuk You; Jae-Mo Yang; Jinkyu Lee; Hong-Goo Kang

doi:10.7776/ASK.2014.33.5.326

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2014 Vol.33, Issue 5 Preview Page Next Page

A Novel Covariance Matrix Estimation Method for MVDR Beamforming In Audio-Visual Communication Systems 오디오-비디오 통신 시스템에서 MVDR 빔 형성 기법을 위한 새로운 공분산 행렬 예측 방법

30 September 2014. pp. 326-334

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Abstract

This paper proposes a novel covariance matrix estimation scheme for minimum variance distortionless response (MVDR) beamforming. By accurately tracking direction-of-sound source arrival (DoA) information using audio-visual sensors, the covariance matrix is efficiently estimated by adopting a variable forgetting factor. The variable forgetting factor is determined by considering signal-to-interference ratio (SIR). Experimental results verify that the performance of the proposed method is superior to that of the conventional one in terms of interference/noise reduction and speech distortion.

Keywords

Audio-visual sensors

MVDR

Beamforming

Covariance matrix

Forgetting factor

본 논문은 MVDR 빔 형성 기법을 위한 새로운 공분산 행렬 예측을 제안한다. 오디오-비디오 센서를 이용하여 음원의 방향 정보를 정확히 추적함으로써, 공분산 행렬은 가변 적응 망각율을 적용하여 효과적으로 예측된다. 가변 적응 망각율은 신호 대 방해 신호 비를 고려하여 결정된다. 실험 결과에서는 제안하는 방법의 성능이 방해신호/잡음 감소 및 음성 왜곡의 면에서 기존의 방법의 성능보다 더 우수하다는 것을 보여준다.

키워드

오디오-비디오 센서

MVDR

빔 형성 기법

공분산 행렬

적응 망각율

References

1.M. Brandstein and D. Ward, Microphone Arrays – Signal Processing Techniques and Applications (Springer-Verlag, Berlin, 2001), pp. 3-17, pp. 229-378.

2.B.D. Van Veen and K.M. Buckley, “Beamforming: a versatile approach to spatial filtering,” ASSP Magazine, IEEE. 5, 4-24 (1988).

3.J. Zhuang, P. Huang, and W. Huang, “Matched direction beamforming based on signal subspace,” in IEEE ICASSP, 2585-2588 (2012).

4.H.K. Maganti, D. Gatica-Perez, and I. McCowan, “Speech enhancement and recognition in meetings with an audio– visual sensor array,” IEEE Trans. on ASLP. 15, 2257-2269 (2007).

5.J. Gu and P.J. Wolfe, “Robust adaptive beamforming using variable loading,” in Workshop on Sensor Array and Multich. Proc. IEEE, 1-5 (2006).

6.J.S. Lee, G.K. You, J.M. Yang, and H.G. Kang, “Unified framework for user tracking and sound beamforming with audio/depth sensors in Kinect,” in Workshop on Kinect in Pervasive Computing, Pervasive 2012, 1-4 (2012).

7.S. Doclo and M. Moonen, “On the output snr of the speech- distortion weighted multichannel wiener filter,” IEEE Signal Proc. Letters 12, 809–811 (2005).

8.J. B. Allen and D. A. Berkley, “Image method for efficiently simulating small-room acoustics,” J. Acoust. Soc. Am. 65, 943–950 (1979).

9.J.Benesty, J. Chen, and Y. Huang, Microphone Array Signal Processing (Springer-Verlag, Berlin, 2009), pp. 86-89.

Information

Publisher :The Acoustical Society of Korea
Publisher(Ko) :한국음향학회
Journal Title :The Journal of the Acoustical Society of Korea
Journal Title(Ko) :한국음향학회지
Volume : 33
No :5
Pages :326-334
Received Date : 2014-02-18
Revised Date : 2014-05-15
Accepted Date : 2014-07-16
DOI :https://doi.org/10.7776/ASK.2014.33.5.326

The Journal of the Acoustical Society of KoreaISSN:1225-4428(Print) 2287-3775(Online)한국음향학회

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