Marcos H. Maruo

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This work presents a statistical analysis of a jointly optimized beamformer-assisted acoustic echo canceler (AEC). It is shown that the constrained joint optimization problem can be formulated so that it becomes equivalent to the linearly-constrained minimum variance problem. The new formulation leads to analytical models that can be used to predict the(More)
Acoustic echo cancellation constitutes a major challenge for full-duplex communication and human-machine speech interaction. Beamforming is a well-known technique for suppression of local interferers, including acoustic echoes. Those techniques can be combined to jointly achieve better echo cancellation at an additional computational cost. Experimental(More)
This work presents a statistical analysis of a beamformer-assisted acoustic echo canceler (AEC). A new formulation leads to analytical models that can also be used to predict the transient performance of adaptive wideband beamformers. Monte Carlo simulations illustrate the accuracy of the model, which is then used to provide design guidelines. Application(More)
Beamformer-assisted acoustic echo cancelers have raised a lot of interest lately. The same performance can be obtained with a reduced length acoustic echo canceler (AEC) as the beamformer (BF) performs spatial cancellation. Structures that jointly optimize the BF and the AEC coefficients are preferred in order to exploit synergies. Analytical models have(More)
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