The MVDR Beamformer for Speech Enhancement

The minimum variance distortionless response (MVDR) beamformer is widely studied in the area of speech enhancement and can be used for both speech dereverberation and noise reduction. This chapter summarizes some new insights into the MVDR beamformer. Specifically, the local and global behaviors of the MVDR beamformer are analyzed, different forms of the MVDR beamformer and relations between the MVDR and other optimal beamformers are discussed. In addition, the tradeoff between dereverberation and noise reduction is analyzed. This analysis is done for a mixture of coherent and non-coherent noise fields and entirely non-coherent noise fields. It is shown that maximum noise reduction is achieved when the MVDR beamformer is used for noise reduction only. The amount of noise reduction that is sacrificed when complete dereverberation is required depends on the directto- reverberation ratio of the acoustic impulse response between the source and the reference microphone. The performance evaluation demonstrates the tradeoff between dereverberation and noise reduction.

[1]  Boaz Rafaely,et al.  Microphone Array Signal Processing , 2008 .

[2]  Ehud Weinstein,et al.  Signal enhancement using beamforming and nonstationarity with applications to speech , 2001, IEEE Trans. Signal Process..

[3]  Sidney Darlington,et al.  Linear least-squares smoothing and prediction, with applications , 1958 .

[4]  B. Breed,et al.  A short proof of the equivalence of LCMV and GSC beamforming , 2002, IEEE Signal Processing Letters.

[5]  Marc Moonen,et al.  Subspace Methods for Multimicrophone Speech Dereverberation , 2003, EURASIP J. Adv. Signal Process..

[6]  Jacob Benesty,et al.  On Microphone-Array Beamforming From a MIMO Acoustic Signal Processing Perspective , 2007, IEEE Transactions on Audio, Speech, and Language Processing.

[7]  Emanuel A. P. Habets,et al.  New Insights Into the MVDR Beamformer in Room Acoustics , 2010, IEEE Transactions on Audio, Speech, and Language Processing.

[8]  O. L. Frost,et al.  An algorithm for linearly constrained adaptive array processing , 1972 .

[9]  J. Capon High-resolution frequency-wavenumber spectrum analysis , 1969 .

[10]  Jacob Benesty,et al.  Adaptive Blind Multichannel Identification , 2008 .

[11]  Jacob Benesty,et al.  New insights into the noise reduction Wiener filter , 2006, IEEE Transactions on Audio, Speech, and Language Processing.

[12]  Andreas Antoniou,et al.  Practical Optimization: Algorithms and Engineering Applications , 2007, Texts in Computer Science.

[13]  Jont B. Allen,et al.  Image method for efficiently simulating small‐room acoustics , 1976 .

[14]  Antonio Cantoni,et al.  Derivative constraints for broad-band element space antenna array processors , 1983 .

[15]  Juro Ohga,et al.  Adaptive microphone-array system for noise reduction , 1986, IEEE Trans. Acoust. Speech Signal Process..

[16]  Michael S. Brandstein,et al.  Microphone Arrays - Signal Processing Techniques and Applications , 2001, Microphone Arrays.

[17]  Marc Moonen,et al.  Frequency-domain criterion for the speech distortion weighted multichannel Wiener filter for robust noise reduction , 2007, Speech Commun..

[18]  P. Peterson Simulating the response of multiple microphones to a single acoustic source in a reverberant room. , 1986, The Journal of the Acoustical Society of America.

[19]  Marc Moonen,et al.  Spatially pre-processed speech distortion weighted multi-channel Wiener filtering for noise reduction , 2003, Signal Process..

[20]  Marc Moonen,et al.  GSVD-based optimal filtering for single and multimicrophone speech enhancement , 2002, IEEE Trans. Signal Process..

[21]  Ea-Ee Jan,et al.  Sound capture from spatial volumes: matched-filter processing of microphone arrays having randomly-distributed sensors , 1996, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings.

[22]  L. J. Griffiths,et al.  An alternative approach to linearly constrained adaptive beamforming , 1982 .

[23]  Jacob Benesty,et al.  On the Importance of the Pearson Correlation Coefficient in Noise Reduction , 2008, IEEE Transactions on Audio, Speech, and Language Processing.

[24]  Sofiène Affes,et al.  A source subspace tracking array of microphones for double talk situations , 1996, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings.

[25]  Henry Cox,et al.  Robust adaptive beamforming , 2005, IEEE Trans. Acoust. Speech Signal Process..

[26]  Israel Cohen,et al.  Performance analysis of dual source transfer-function generalized sidelobe canceller , 2007, Speech Commun..

[27]  Alan V. Oppenheim,et al.  Discrete-time signal processing (2nd ed.) , 1999 .