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 letter describes algorithms for nonnegative matrix factorization (NMF) with the β-
divergence (β-NMF). The β-divergence is a family of cost functions parameterized by a …

This paper presents new formulations and algorithms for multichannel extensions of non-
negative matrix factorization (NMF). The formulations employ Hermitian positive semidefinite …

This paper addresses the estimation of the latent dimensionality in nonnegative matrix
factorization (NMF) with the (β)--divergence. The (β)-divergence is a family of cost functions …

We propose a class of multiplicative algorithms for Nonnegative Matrix Factorization (NMF)
which are robust with respect to noise and outliers. To achieve this, we formulate a new …

We introduce a robust mixing model to describe hyperspectral data resulting from the
mixture of several pure spectral signatures. The new model extends the commonly used …

This letter proposes a multichannel source separation technique, the multichannel
variational autoencoder (MVAE) method, which uses a conditional VAE (CVAE) to model …

When designing an audio processing system, the target tasks often influence the choice of a
data representation or transformation. Low-level time-frequency representations such as the …

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 …

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