This paper describes several important methods for the blind source separation of audio
signals in an integrated manner. Two historically developed routes are featured. One started …

This paper addresses the determined blind source separation problem and proposes a new
effective method unifying independent vector analysis (IVA) and nonnegative matrix …

In this chapter, we provide an overview of existing algorithms for blind source separation of
convolutive audio mixtures. We provide a taxonomy in which many of the existing algorithms …

In this paper, we propose a new framework called independent deeply learned matrix
analysis (IDLMA), which unifies a deep neural network (DNN) and independence-based …

In this chapter, we address the determined blind source separation problem and introduce a
new effective method of unifying independent vector analysis (IVA) and nonnegative matrix …

We propose a new blind spatial subtraction array (BSSA) consisting of a noise estimator
based on independent component analysis (ICA) for efficient speech enhancement. In this …

Blind source separation (BSS) methods have received extensive attention over the past two
decades; thanks to its wide applicability in a number of areas such as biomedical …

In this paper, we show that minimization of the statistical dependence using broadband
independent component analysis (ICA) can be successfully exploited for acoustic source …

A novel multimodal approach is proposed to solve the problem of blind source separation
(BSS) of moving sources. The challenge of BSS for moving sources is that the mixing filters …

This paper addresses the multichannel directional speech enhancement problem with
geometrically constrained independent vector analysis (GCIVA), where we aim to combine …