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 article describes a computationally-efficient blind source separation (BSS) method
based on the independence, low-rankness, and directivity of the sources. A typical approach …

This paper describes a semi-supervised multichannel speech enhancement method that
uses clean speech data for prior training. Although multichannel nonnegative matrix …

This paper describes a versatile method that accelerates multichannel source separation
methods based on full-rank spatial modeling. A popular approach to multichannel source …

A multichannel extension of nonnegative matrix factorization (NMF) for audio/music data,
called multichannel NMF (MNMF), has been proposed by Sawada et al [" Multichannel …

This paper proposes harmonic vector analysis (HVA) based on a general algorithmic
framework of audio blind source separation (BSS) that is also presented in this paper. BSS …

This paper addresses the determined convolutive blind source separation (BSS) problem.
The state-of-the-art independent low-rank matrix analysis (ILRMA), unifying independent …

This paper describes a joint blind source separation and dereverberation method that works
adaptively and efficiently in a reverberant noisy environment. The modern approach to blind …

Independent low-rank matrix analysis (ILRMA) is the state-of-the-art algorithm for blind
source separation (BSS) in the determined situation (the number of microphones is greater …

We present a unifying framework for dealing with convolutive blind source separation (BSS),
which fully models inter-channel, inter-frequency, and inter-frame correlation of sources by …