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.
Hussain
A
A
Department of Applied Computing, University of Dundee, Scotland, UK.
D000161:Acoustic Stimulation; D000465:Algorithms; D001303:Auditory Cortex / Q000502:physiology; D001336:Automobiles; D003198:Computer Simulation; D006801:Humans; D016571:Neural Networks, Computer; D009622:Noise; D017711:Nonlinear Dynamics; D012815:Signal Processing, Computer-Assisted; D013067:Speech Perception