Multi-sensor neural-network processing of noisy speech

In this paper, a novel Artificial Neural-Network (ANN) based multi-sensor multi-band adaptive signal-processing scheme is described for enhancing acoustic-speech corrupted by real noise and reverberation. Numerically robust adaptation-algorithms are employed for the ANN based sub-band filters; and, new simulation experiments are reported using real-reverberant automobile data which demonstrate that the proposed speech-enhancement system is capable of outperforming conventional linear filtering-based wide-band and multi-band noise-cancellation schemes.