The performance of traditional voice activity detectors significantly deteriorates in the
presence of highly nonstationary noise and transient interferences. One solution is to …

We address voice activity detection in acoustic environments of transients and stationary
noises, which often occur in real-life scenarios. We exploit unique spatial patterns of speech …

We address the problem of voice activity detection in difficult acoustic environments
including high levels of noise and transients, which are common in real life scenarios. We …

In this paper, we address the problem of multiple view data fusion in the presence of noise
and interferences. Recent studies have approached this problem using kernel methods, by …

Voice activity detection in the presence of transient interferences is a challenging problem
since transients are often detected incorrectly as speech by existing detectors. In this paper …

In this paper, we apply the scattering transform (ST)—a nonlinear map based off of a
convolutional neural network (CNN)—to classification of underwater objects using sonar …

Abstract The Scattering Transform (ST) is a formalization of some potential properties that
have made convolutional neural networks effective at a wide variety of image and signal …

A fundamental problem in multimodal signal processing is to quantify relations between two
different signals with respect to a certain phenomenon. In this paper, we address this …

Appearance-based feature extraction constitutes the dominant approach for visual speech
representation in a variety of problems, such as automatic speechreading, visual speech …

We consider a problem setup, in which a desired speech source is measured by a
microphone and by a video camera in an interfering environment. We assume that the …