Blind source separation combining independent component analysis and beamforming
EURASIP Journal on Applied Signal Processing
EURASIP Journal on Applied Signal Processing
Permutation correction in the frequency domain in blind separation of speech mixtures
EURASIP Journal on Applied Signal Processing
EURASIP Journal on Applied Signal Processing
Performance evaluation of blind source separation schemes in anechoic and echoic environments
ISPRA'08 Proceedings of the 7th WSEAS International Conference on Signal Processing, Robotics and Automation
Estimating Phase Linearity in the Frequency-Domain ICA Demixing Matrix
ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
Combination of adaptive feedback cancellation and binaural adaptive filtering in hearing aids
EURASIP Journal on Advances in Signal Processing - Special issue on digital signal processing for hearing instruments
Underdetermined convolutive blind source separation via time-frequency masking
IEEE Transactions on Audio, Speech, and Language Processing
Real-time independent vector analysis for convolutive blind source separation
IEEE Transactions on Circuits and Systems Part I: Regular Papers
Blind source separation using variable step-size adaptive algorithm in frequency domain
SSIP'05 Proceedings of the 5th WSEAS international conference on Signal, speech and image processing
ISNN'05 Proceedings of the Second international conference on Advances in neural networks - Volume Part II
Complex FastIVA: a robust maximum likelihood approach of MICA for convolutive BSS
ICA'06 Proceedings of the 6th international conference on Independent Component Analysis and Blind Signal Separation
Stability of independent vector analysis
Signal Processing
Modulation domain blind speech separation in noisy environments
Speech Communication
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This paper describes a new blind signal separation method using the directivity patterns of a microphone array. In this method, to deal with the arriving lags among each microphone, the inverses of the mixing matrices are calculated in the frequency domain so that the separated signals are mutually independent. Since the calculations are carried out in each frequency independently, the following problems arise: (1) permutation of each sound source, (2) arbitrariness of each source gain. In this paper, we propose a new solution that directivity patterns are explicitly used to estimate each sound source direction. As the results of signal separation experiments, it is shown that the proposed method improves the SNR of degraded speech by about 16 dB under non-reverberant condition. Also, the proposed method improves the SNR by 8.7 dB when the reverberation time is 184 ms, and by 5.1 dB when the reverberation time is 322 ms.