Distributed multichannel Wiener filtering for speech enhancement in acoustic sensor networks

The performance of speech processing algorithms in wireless acoustic sensor networks (WASNs) is severely degraded by diffuse noise. To address this problem, a distributed speech enhancement algorithm for WASNs is proposed in this article. The parameterized multichannel Wiener filter is first improved by exploiting all cross-correlation information among nodes. Next, using the Hadamard element-wise product of label matrix and cross-correlation matrix, the distributed parameterized multichannel Wiener filter based on the in-network summation is presented. Moreover, by making the tradeoff between communication cost and enhancement performance, a simplified distributed algorithm is proposed. Finally, the noise reduction performance of the proposed method is theoretically analyzed. The proposed method achieves good speech enhancement performance and requires only in-network summation in WASNs. Experimental results reveal the validity of the proposed method.