Multi-task wireless acoustic sensor network for node-specific speech enhancement and DOA estimation

Amin Hassani, J. Plata-Chaves, A. Bertrand, M. Moonen
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引用次数: 4

Abstract

We consider the design of a distributed algorithm that is suitable for a wireless acoustic sensor network formed by nodes solving multiple tasks (MDMT). In the network, some of the nodes aim at estimating the node-specific direction-of-arrival of some desired sources. Additionally, there are other nodes that aim at implementing either a multi-channel Wiener filter or a minimum variance distortionless response beamformer in order to estimate node-specific desired signals as they impinge on their microphones. By using compressive filter-and-sum operations that incorporate a low-rank approximation of the sensor signal correlation matrix, the proposed MDMT algorithm let the nodes cooperate to achieve the network-wide centralized solution of their node-specific estimation problems without any knowledge about the tasks of other nodes. Finally, the effectiveness of the algorithm is shown through computer simulations.
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多任务无线声学传感器网络中特定节点的语音增强和DOA估计
我们考虑设计一种适用于由节点求解多任务(MDMT)组成的无线声学传感器网络的分布式算法。在网络中,一些节点的目的是估计某些期望源的节点特定的到达方向。此外,还有其他节点旨在实现多通道维纳滤波器或最小方差无失真响应波束形成器,以便在信号冲击麦克风时估计节点特定的期望信号。通过使用压缩滤波和运算,结合传感器信号相关矩阵的低秩近似,所提出的MDMT算法让节点合作,在不了解其他节点任务的情况下,实现其节点特定估计问题的全网集中解决。最后,通过计算机仿真验证了该算法的有效性。
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