Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications
Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications
ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
Multichannel nonnegative matrix factorization in convolutive mixtures for audio source separation
IEEE Transactions on Audio, Speech, and Language Processing
Complex nonconvex lp norm minimization for underdetermined source separation
ICA'07 Proceedings of the 7th international conference on Independent component analysis and signal separation
The 2011 signal separation evaluation campaign (SiSEC2011): - audio source separation -
LVA/ICA'12 Proceedings of the 10th international conference on Latent Variable Analysis and Signal Separation
Convolutive BSS of Short Mixtures by ICA Recursively Regularized Across Frequencies
IEEE Transactions on Audio, Speech, and Language Processing
Blind Spatial Subtraction Array for Speech Enhancement in Noisy Environment
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
Generalized State Coherence Transform for Multidimensional TDOA Estimation of Multiple Sources
IEEE Transactions on Audio, Speech, and Language Processing
The 2011 signal separation evaluation campaign (SiSEC2011): - audio source separation -
LVA/ICA'12 Proceedings of the 10th international conference on Latent Variable Analysis and Signal Separation
Structured Sparsity Models for Reverberant Speech Separation
IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP)
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This paper presents a novel method for underdetermined acoustic source separation of convolutive mixtures. Multiple complex-valued Independent Component Analysis adaptations jointly estimate the mixing matrix and the temporal activities of multiple sources in each frequency. A structure based on a recursive temporal weighting of the gradient enforces each ICA adaptation to estimate mixing parameters related to sources having a disjoint temporal activity. Permutation problem is reduced imposing a multiresolution spatio-temporal correlation of the narrow-band components. Finally, aligned mixing parameters are used to recover the sources through L0 -norm minimization and a post-processing based on a single channel Wiener filtering. Promising results obtained over a public dataset show that the proposed method is an effective solution to the underdetermined source separation problem.