  We describe a joint acoustic echo cancellation (AEC) and blind source
extraction (BSE) approach for multi-microphone acoustic frontends. The proposed
algorithm blindly estimates AEC and beamforming filters by maximizing the
statistical independence of a non-Gaussian source of interest and a stationary
Gaussian background modeling interfering signals and residual echo. Double
talk-robust and fast-converging parameter updates are derived from a global
maximum-likelihood objective function resulting in a computationally efficient
Newton-type update rule. Evaluation with simulated acoustic data confirms the
benefit of the proposed joint AEC and beamforming filter estimation in
comparison to updating both filters individually.
