Independent component analysis: theory and applications
Independent component analysis: theory and applications
Convolutive blind separation of speech mixtures using the natural gradient
Speech Communication - Special issue on speech processing for hearing aids
Blind Separation of Multiple Speakers in a Multipath Environment
ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97) -Volume 1 - Volume 1
Blind Source Separation of Convolutive Mixtures of Speech in Frequency Domain
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Computational Auditory Scene Analysis: Principles, Algorithms, and Applications
Computational Auditory Scene Analysis: Principles, Algorithms, and Applications
Limitations of the Spectrum Masking Technique for Blind Source Separation
ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
A multistage approach for blind separation of convolutive speech mixtures
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
Post-processing for frequency-domain blind source separation in hearing aids
ICICS'09 Proceedings of the 7th international conference on Information, communications and signal processing
Underdetermined convolutive blind source separation via time-frequency masking
IEEE Transactions on Audio, Speech, and Language Processing
IEEE Transactions on Signal Processing
A frequency domain blind signal separation method based ondecorrelation
IEEE Transactions on Signal Processing
IEEE Transactions on Audio, Speech, and Language Processing
Blind Separation of Underdetermined Convolutive Mixtures Using Their Time–Frequency Representation
IEEE Transactions on Audio, Speech, and Language Processing
Spatio–Temporal FastICA Algorithms for the Blind Separation of Convolutive Mixtures
IEEE Transactions on Audio, Speech, and Language Processing
Convolutive Blind Source Separation in the Frequency Domain Based on Sparse Representation
IEEE Transactions on Audio, Speech, and Language Processing
IEEE Transactions on Audio, Speech, and Language Processing
Blind Extraction of Dominant Target Sources Using ICA and Time-Frequency Masking
IEEE Transactions on Audio, Speech, and Language Processing
Monaural speech segregation based on pitch tracking and amplitude modulation
IEEE Transactions on Neural Networks
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We propose a novel algorithm for the separation of convolutive speech mixtures using two-microphone recordings, based on the combination of independent component analysis (ICA) and ideal binary mask (IBM), together with a post-filtering process in the cepstral domain. The proposed algorithm consists of three steps. First, a constrained convolutive ICA algorithm is applied to separate the source signals from two-microphone recordings. In the second step, we estimate the IBM by comparing the energy of corresponding time-frequency (T-F) units from the separated sources obtained with the convolutive ICA algorithm. The last step is to reduce musical noise caused by T-F masking using cepstral smoothing. The performance of the proposed approach is evaluated using both reverberant mixtures generated using a simulated room model and real recordings in terms of signal to noise ratio measurement. The proposed algorithm offers considerably higher efficiency and improved speech quality while producing similar separation performance compared with a recent approach.