Adaptive, acoustic noise suppression for speech enhancement

Removal of ambient noise from a single-channel audio signal is becoming an increasingly important problem due to the proliferation of portable communication devices. Furthermore, in applications such as wireless telephony and phonetic data mining, it is desired that noise suppression be robust to changing noise conditions and that processing take place in real time or faster. This paper proposes an adaptive noise suppression system that mitigates or eliminates processing artifacts common to Wiener filtering without decreasing speech recognition performance. Results of one implementation of such a structure demonstrate significant improvements in both perceptual quality and speech recognition performance under noisy conditions.