Reverberant speech separation with probabilistic timefrequency masking for B-format recordings
We have presented a new algorithm for the separation of convolutive mixtures by incorporating the intensity vector of the acoustic field with probabilistic timefrequency masking. The DOA and mixing vector cues are modeled by the von Mises mixture model and complex Gaussian mixture model respectively, the parameters of which are updated iteratively via the EM algorithm. A reliability-based method is introduced to improve the performance of source separation by mitigating the effect of room reverberation.
b-format signal acoustic intensity expectationmaximization (em) algorithm blind source separation (bss) direction of arrival (doa)