A wireless acoustic sensor network is considered with spatially distributed microphones which observe a desired speech signal that has been corrupted by noise. In order to reduce the noise the signals are sent to a fusion center where they are processed with a centralized rank-1 multi-channel Wiener filter (R1-MWF). The goal of this work is to efficiently compute an assessment of the contribution of each individual microphone with respect to either signal-to-noise ratio (SNR), signal-to-distortion ratio (SDR) or the minimized cost function referred to as the utility. These performance measures are derived by exploiting unique properties of the R1-MWF which can be computed efficiently from values that are known from the current signal estimation process. The performance measures may be used in unison or individually to determine the contributions of each microphone and help facilitate in selecting only a subset of the available signals in order to meet the bandwidth and power constraints of the system.
['Joseph Szurley', 'Alexander Bertrand', 'Marc Moonen']
Efficient computation of microphone utility in a wireless acoustic sensor network with multi-channel Wiener filter based noise reduction