5 accepted papers
Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system. It affects cognitive and motor functions, and the limitation of executive functions can also manifest itself in speech production. Due to this, automatic speech analysis might serve as an effective technique for…
Dementia is a chronic or progressive clinical syndrome, mainly characterized by the deterioration of memory, thinking, reasoning and language. In Mild cognitive impairment (MCI), often considered as the prodromal stage of dementia, there is also a subtle deterioration of these functions, but they do…
State-of-the-art silent speech interface systems apply vocoders to generate the speech signal directly from articulatory data. Most of these approaches concentrate on estimating just the spectral features of the vocoder, and use the original F0, a constant F0 or white noise as excitation. This solut…
Deep neural network (DNN) based speech recognizers have recently replaced Gaussian mixture (GMM) based systems as the state-of-the-art. HMM/DNN systems have kept many refinements of the HMM/GMM framework, even though some of these may be suboptimal for them. One such example is the creation of conte…
The deep neural network component of current hybrid speech recognizers is trained on a context of consecutive feature vectors. Here, we investigate whether the time span of this input can be extended by splitting it up and modeling it in smaller chunks. One method for this is to train a hierarchy of…