A new metric for selecting sub-band processing in adaptive speech enhancement systems

A multi-microphone adaptive speech enhancement system employing diverse sub-band processing is presented. A new robust metric is developed, which is capable of real-time implementation, in order to automatically select the best form of processing within each sub-band. It is based on an adaptively estimated inter-channel Magnitude Squared Coherence (MSC) relationship, which is used to detect the level of correlation between in-band signals from multiple sensors during noise-alone periods in intermittent speech. This paper reports recent results of comparative experiments with simulated anechoic data extended to include simulated reverberant data. The results demonstrate that the method is capable of significantly outperforming conventional noise cancellation schemes.