抽象的

Combining Beam forming and BSS to improve Source Separation Performance

R. Ruben Johnson, S. Aishwarya

Beam forming (BF) and Blind Source Separation (BSS) are always two interesting methodologies to witness in order to separate two sources. BSS in frequency domain have been facing a serious issue of permutation ambiguity while performing source separation using Independent Component Analysis (ICA). Permutation Ambiguity is a problem of mismatch of any frequency lines between the sources, so the separation in the time domain cannot exhibit a perfect separation due to the frequency components of other sources present in the time signal of one source. Various methods have been adopted all through the years of research to get rid of this critical issue and no perfect results are produced so far. The proposed method of combining BF to BSS seems to be a good approach as BF mainly depends on time difference of arrival information (delay) between the reference microphone to the consecutive microphones. The original delay information is compared to the estimated delays for each frequency lines in order to realign the frequency lines if they see a permutation by ICA. So, there is no possibility of frequency mismatch still existing when the delay information is operated as a major concern. The performance is measured using Signal to Interference Ratio measurement where Beamforming approach seems to have an improved performance compared to other existing methods. Simulation results show performance comparison. The algorithm is tested using two speech sources in a free field environment. We use Short Time Fourier Transform (STFT) for frequency domain transformation