  For multichannel speech enhancement, this letter derives a robust maximum
likelihood distortionless response beamformer by modeling speech sparse priors
with a complex generalized Gaussian distribution, where we refer to as the
CGGD-MLDR beamformer. The proposed beamformer can be regarded as a
generalization of the minimum power distortionless response beamformer and its
improved variations. For narrowband applications, we also reveal that the
proposed beamformer reduces to the minimum dispersion distortionless response
beamformer, which has been derived with the ${{\ell}_{p}}$-norm minimization.
The mechanisms of the proposed beamformer in improving the robustness are
clearly pointed out and experimental results show its better performance in
PESQ improvement.
