In this paper, we generalize the notions of centroids (and barycenters) to the broad class of
information-theoretic distortion measures called Bregman divergences. Bregman …

Sign language recognition involves modeling of multichannel information such as, hand
shapes, hand movements. This requires also sufficient sign language specific data. This is a …

This paper addresses the problem of recognizing the speech uttered by patients with
dysarthria, which is a motor speech disorder impeding the physical production of speech …

Over the past few decades, the rate of diagnosing depression and mental illness among
youths in both genders has been emerging as a challenging issue in the present society …

In the literature, the task of dysarthric speech intelligibility assessment has been approached
through development of different low-level feature representations, subspace modeling …

Posterior probabilities of sub-word units have been shown to be an effective front-end for
ASR. However, attempts to model this type of features either do not benefit from modeling …

In this chapter, we describe one of the several possible ways of exploiting deep neural
networks (DNNs) in automatic speech recognition systems—the deep neural network …

Phonological studies suggest that the typical subword units such as phones or phonemes
used in automatic speech recognition systems can be decomposed into a set of features …

We propose a novel multi-stream framework for continuous conversational speech
recognition which employs bidirectional Long Short-Term Memory (BLSTM) networks for …

Deep architectures have recently been explored in hybrid hidden Markov model/artificial
neural network (HMM/ANN) framework where the ANN outputs are usually the clustered …