Divergence measures for statistical data processing—An annotated bibliography -
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This article addresses the problem of multichannel audio source separation. We propose a
framework where deep neural networks (DNNs) are used to model the source spectra and …

Reducing the interference noise in a monaural noisy speech signal has been a challenging
task for many years. Compared to traditional unsupervised speech enhancement methods …

Statistical models usually require vector representations of categorical variables, using for
instance one-hot encoding. This strategy breaks down when the number of categories …

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 …

Nonnegative matrix factorization (NMF) has become a popular dimension-reduction method
and has been widely applied to image processing and pattern recognition problems …

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

We propose a unified and systematic framework for performing online nonnegative matrix
factorization in the presence of outliers. Our framework is particularly suited to large-scale …

Robust segmentation of hands in a cluttered environment for hand gesture recognition has
remained a challenge in computer vision. In this work, a two-stage gesture recognition …

In this paper, we present an on-line semi-supervised algorithm for real-time separation of
speech and background noise. The proposed system is based on Nonnegative Matrix …