6 accepted papers
Depression is a frequent and curable psychiatric disorder, detrimentally affecting daily activities, harming both work-place productivity and personal relationships. Among many other symptoms, depression is associated with disordered speech production, which might permit its automatic screening by m…
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…
Estimating the degree of sleepiness from the human speech is an emerging research problem with straightforward applications. In this study, we employ the x-vector approach, currently the state-of-the-art in speaker recognition, as a neural network feature extractor to detect the level of sleepiness…
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…