A real time robust adaptive microphone array controlled by an SNR estimate

DOA-informed source extraction in the presence of competing talkers and background noise

“…The estimators given by (9) and (12) assume that for each microphone pair, the spatial aliasing frequency lies above F s 2 , where F s is the sampling rate. Alternatively, frequency-dependent binary weights can be used to exclude microphone pairs at the frequency bins where spatial aliasing might occur for those pairs, as done in [27].…”

“…RABs can also be implemented in a general sidelobe canceler (GSC) structure, where the robustness to DOA and propagation vector mismatches is ensured by using an adaptive blocking matrix [10,11], and by imposing constraints to the adaptive noise cancellers [10]. The robust GSCs require a desired signal detector, as the noise cancellers need to be updated when the desired signal is absent, while the blocking matrix when the desired signal is present [12].…”

An acoustic front-end for interactive TV incorporating multichannel acoustic echo cancellation and blind signal extraction

“…To this end, directional BSS is superior to conventional beamforming techniques, e.g., null-beamformers, in suppressing the target signal located at φtar, especially in reverberant environments (see [9]). Moreover, in contrast to many beamformer techniques, e.g., [10], [11], no voice-activity detector is needed and no prior knowledge on the microphone positions is required. The directional constraint as given in (4) forces a spatial null towards the desired source location which has to be estimated or known a priori in real applications.…”

Application of the maximum signal to interference ratio criterion to the adaptive microphone array

“…The interference matrix ⌽ u , can be estimated within pauses of the desired speech that can be detected by the pause detector. [4][5][6] Since interference is almost always present, an estimation of the matrix ⌽ s is somewhat more complicated. A reasonable approach might be to select time intervals where the signal-to-interference ratio is high and use these intervals for estimating the ⌽ s .…”

“…1,2 The common drawback of the MV-based adaptive microphone arrays is their sensitivity to the room reverberation that causes the cancellation of the desired speech signal. [3][4][5] This cancellation can be prevented if the weight vector is estimated within pauses of the desired speech. 5,6 The results presented in this paper will demonstrate that the quality of the restored speech signal can be further improved by applying the maximum signal to interference ratio (MSIR) criterion for weight vector estimation.…”