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 aneural blind source separation (BSS) method based on amortized
variational inference (AVI) of a non-linear generative model of mixture signals. A classical …

Blind source separation (BSS) of audio signals aims to separate original source signals from
their mixtures recorded by microphones. The applications include automatic speech …

This paper describes multichannel speech enhancement for improving automatic speech
recognition (ASR) in noisy environments. Recently, the minimum variance distortionless …

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

Nonnegative matrix factorization (NMF) has been traditionally considered a promising
approach for audio source separation. While standard NMF is only suited for single-channel …

In this paper, we address the problem of extracting all super-Gaussian source signals from a
linear mixture in which (i) the number of super-Gaussian sources K is less than that of …

This article describes a computationally-efficient statistical approach to joint (semi-) blind
source separation and dereverberation for multichannel noisy reverberant mixture signals. A …

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 …

Overlap** speech and high room reverberation deteriorate the accuracy of automatic
speech recognition (ASR). This paper proposes a method for jointly optimum source …