High dimensional data arising from diverse scientific research fields and industrial
development have led to increased interest in sparse learning due to model parsimony and …

We tackle the speech separation problem through modeling the acoustics of the reverberant
chambers. Our approach exploits structured sparsity models to perform speech recovery and …

This paper addresses the problem of ad hoc microphone array calibration where only partial
information about the distances between microphones is available. We construct a matrix …

In this paper, the problem of multiple speaker localization via speech separation based on
model-based sparse recovery is studies. We compare and contrast computational sparse …

Spatial filtering is the fundamental characteristic of microphone array based signal
acquisition, which plays an important role in applications such as speech enhancement and …

In this paper, we investigate the diffuse field coherence model for microphone array pairwise
distance estimation. We study the fundamental constraints and assumptions underlying this …

This thesis takes place in the context of multi-microphone distant speech recognition in
multiparty meetings. It addresses the fundamental problem of overlapping speech …

We cast the under-determined convolutive speech separation as sparse approximation of
the spatial spectra of the mixing sources. In this framework we compare and contrast the …

This paper addresses the application of missing data recovery via matrix completion for
audio sensor networks. We propose a method based on Euclidean distance matrix …

Although exemplar based approaches have shown good accuracy in classification
problems, some limitations are observed in the accuracy of exemplar based automatic …