Real-time source separation based on sound localization in a reverberant environment

We propose a real-time source separation method that works well even under reverberant conditions. Previously, we proposed a method called SAFIA, which segregates sound sources by using sound localization cues acquired by multiple microphones. Under reverberant conditions, SAFIA suffers from "spectral overlap caused by reverberation", which introduces distortion into the separated speech signals. Extending the concept of SAFIA, we propose a new method (WAFD-SAFIA) based on simple signal-processing operations. WAFD-SAFIA significantly reduces the effects of "spectral overlap caused by reverberation". Computing the SNR (signal-to-noise ratio) and SDR (signal-to-distortion ratio) for both methods, we found that this new method outperformed SAFIA in a realistic environment. Moreover, to clarify the effect of frequency resolution on SAFIA, we determined whether a given frequency resolution decreased the overlap between the frequency components of two speech signals.