EURASIP Journal on Applied Signal Processing
The role of high frequencies in convolutive blind source separation of speech signals
ICA'07 Proceedings of the 7th international conference on Independent component analysis and signal separation
Blind adaptive wideband beamforming for circular arrays based on phase mode transformation
Digital Signal Processing
Sparse coding for convolutive blind audio source separation
ICA'06 Proceedings of the 6th international conference on Independent Component Analysis and Blind Signal Separation
Blind Deconvolution of Sources in Fourier Space Based on Generalized Laplace Distribution
International Journal of System Dynamics Applications
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We describe a new method of blind source separation (BSS) on a microphone array combining subband independent component analysis (ICA) and beamforming. The proposed array system consists of the following three sections: (1) subband-ICA-based BSS section with direction-of-arrival (DOA) estimation; (2) null beamforming section based on the estimated DOA information; and (3) integration of (1) and (2) based on the algorithm diversity. Using this technique, we can resolve the low-convergence problem through optimization in ICA. The results of the signal separation experiments reveal that a noise reduction rate (NRR) of about 18 dB is obtained under the nonreverberant condition, and NRR of 8 dB and 6 dB are obtained in the case that the reverberation times are 150 msec and 300 msec. These performances are superior to those of both simple ICA-based BSS and simple beamforming method.