Blind source separation is a signal processing method based on independent component analysis, its aim is to separate the source signals from a set of observations (output of sensors) by assuming the source signals independently. This paper reviews the general concept of BSS firstly; especially the theory for convolutive mixtures, the model of convolutive mixture and two deconvolution structure...

A frequency bin-wise nonlinear masking algorithm is proposed in the spectrogram domain for speech segregation in convolutive mixtures. The contributive weight from each speech source to a time-frequency unit of the mixture spectrogram is estimated by a nonlinear function based on location cues. For each sound source, a non-binary mask is formed from the estimated weights and is multiplied to th...

This paper aims to solve the problem of Blind Signal Separation (BSS) in a convolutive environment based on output correlation matrix diagonalization. Firstly an extension of the closed form gradient and Newton methods used by Joho and Rahbar [1] is developed which encapsulates the more difficult convolutive mixing case. This extension is completely in the time domain and thus avoids the inhere...

This paper deals with blind speech separation of convolutive mixtures of sources. The separation criterion is based on Oriented Principal Components Analysis (OPCA) in the frequency domain. OPCA is a (second order) extension of standard Principal Component Analysis (PCA) aiming at maximizing the power ratio of a pair of signals. The convolutive mixing is obtained by modeling the Head Related Tr...

It is well known that the performance of an automatic speaker recognition system degrades in the presence of noise. The degradation of voice due to the presence of additive background noise and convolutive noise causes severe difficulties in various communication environments. This paper addresses the problem of reduction of additive as well as convolutive noise in speech. This paper explores a...

The association of 5',8-cyclo-2'-deoxyguanosine (cdG), a DNA tandem lesion, with its complementary base cytosine has been studied by voltammetry and NMR in chloroform, using properly silylated derivatives of the two nucleobases for increasing their solubilities. Both voltammetric data and NMR titrations indicated that the Watson-Crick complex of cytidine with cdG is weaker than that with guanos...

There are very few techniques that can separate signals from the convolutive mixture in the underdetermined case. We have developed a method that uses overcomplete expansion of the signal created with a time-frequency transform and that also uses the property of sparseness and a Laplacian source density model to obtain the source signals from the instantaneously mixed signals in the underderdet...

We address the problem of blind separation of instantaneous and convolutive mixtures of independent signals. We formulate this problem as an optimization problem using the mutual information criterion. In the case of instantaneous mixtures, we solve the resulting optimization problem with an extended Newton’s method on the Stiefel manifold. This approach works for general independent signals an...

Convolutive mixtures of images are common in photography of semi-reflections. They also occur in microscopy and tomography. Their formation process involves focusing on an object layer, over which defocused layers are superimposed. Blind source separation (BSS) of convolutive image mixtures by direct optimization of mutual information is very complex and suffers from local minima. Thus, we devi...

We consider the problem of convolutive blind source separation of audio mixtures. We propose an Adaptive Stereo Basis (ASB) method based on learning a set of basis vectors pairs from the time-domain stereo mixtures. The basis vector pairs are clustered using estimated directions of arrival (DOAs) such that each basis vector pair is associated with one source. The ASB method is compared with the...