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This paper introduces a novel low-latency online beamforming (BF) algorithm,named Modified Parametric Multichannel Wiener Filter (Mod-PMWF), for enhancingspeech mixtures with unknown and varying number of speakers. Althoughconventional BFs such as linearly constrained minimum variance BF (LCMV BF) canenhance a speech mixture, they typically require such attributes of the speechmixture as the number of speakers and the acoustic transfer functions (ATFs)from the speakers to the microphones. When the mixture attributes areunavailable, estimating them by low-latency processing is challenging,hindering the application of the BFs to the problem. In this paper, we overcomethis problem by modifying a conventional Parametric Multichannel Wiener Filter(PMWF). The proposed Mod-PMWF can adaptively form a directivity pattern thatenhances all the speakers in the mixture without explicitly estimating theseattributes. Our experiments will show the proposed BF's effectiveness ininterference reduction ratios and subjective listening tests.

Modified Parametric Multichannel Wiener Filter \\for Low-latency Enhancement of Speech Mixtures with Unknown Number of Speakers