Fast Convergence Blind Source Separation Based on Frequency Subband Interpolation by Null Beamforming

We propose a new algorithm for blind source separation (BSS) approach that combines independent component analysis (ICA) and frequency subband beamforming interpolation. The slow convergence of the optimization of the separation filters is a problem in ICA. Our approach to resolve this problem is based on the relationship between ICA and null beamforming (NBF). The proposed method consists of the following three parts: (I) a frequency subband selector part for learning ICA, (II) a frequency domain ICA part with direction-of-arrivals (DOA) estimation of sound sources, and (III) an interpolation part using null beamforming constructed with the estimated DOA. In the results of the signal separation experiments under a reverberant condition reveal that the convergence speed is superior to that of the conventional ICA based BSS methods.