We address the problem of blind source separation in the underdetermined mixture case. Two statistical tests are proposed to reduce the number of empirical parameters involved in standard sparsenessbased underdetermined blind source separation (UBSS) methods. The first test performs multisource selection of the suitable time-frequency points for source recovery and is full automatic. The second...

A class of methods based on multichannel linear prediction (MCLP) can achieve effective blind dereverberation of a source, when the source is observed with a microphone array. We propose an inventive use of MCLP as a pre-processing step for blind source separation with a microphone array. We show theoretically that, under certain assumptions, such pre-processing reduces the original blind rever...

This paper presents a method for solving the permutation problem of frequency domain blind source separation (BSS) when the number of source signals is large, and the potential source locations are omnidirectional. We propose a combination of small and large spacing sensor pairs with various axis directions in order to obtain proper geometric information for solving the permutation problem. Exp...

Recognition of planar objects from their images taken from different viewpoints requires affine invariants calculated from the object boundaries. The equivalence between affine transformation and the source mixture model simplifies the recognition problem. The rotation, scaling, skewing, and translation effects of the affine transformation can be undone by using blind source separation (BSS) te...

Family separation is a practice rooted in U.S. history. In order to comprehensively examine the most recent execution of separating children from their parents under Trump Administration’s “zero tolerance” policy, one must follow and understand this That what Article does. Examining histories enslaved, Indigenous, immigrant families, it offers critical context reoccurring that has had devastati...

In this paper, we evaluate the usefulness of several monaural blind source separation (BSS) algorithms in the context of vocal detection (VD). BSS is the problem of recovering several sources, given only a mixture. VD is the problem of automatically identifying the parts in a mixed audio signal, where at least one person is singing. We compare the results of three different strategies for utili...