The present invention is a new approach to residual echo spectrum modeling for nonlinear residual acoustic echo suppression. Low-dimensional features are computed from the far-end signal and used as input to the network containing linear and possibly non-linear elements. The network parameters can be optimized “offline” using recorded training data and/or applied “online” using other methods that can be effectively implemented in real time.
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