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 …

Under-resourced speech recognizers may benefit from data in languages other than the
target language. In this paper, we report how to boost the performance of an Afrikaans …

The paper discusses an approach for dealing with unexpected acoustic elements in speech.
The approach is motivated by observations of human performance on such problems, which …

Setting out from the point of view that automatic speech recognition (ASR) ought to benefit
from data in languages other than the target language, we propose a novel Kullback-Leibler …

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 …

This paper studies cross-lingual acoustic modeling in the context of subspace Gaussian
mixture models (SGMMs). SGMMs factorize the acoustic model parameters into a set that is …

In this paper, a compressive sensing (CS) perspective to exemplar-based speech
processing is proposed. Relying on an analytical relationship between CS formulation and …