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In this article, we present our findings from ten years of research on intelligent educational games. We discuss the architecture of our training environments for learning spelling and mathematics, and specifically focus on the representation of the conten ...
The goal of this thesis is to improve current state-of-the-art techniques in speaker verification
(SV), typically based on âidentity-vectorsâ (i-vectors) and deep neural network (DNN), by exploiting diverse (phonetic) information extracted using variou ...
In this article, we present our findings from ten years of research on intelligent educational games. We discuss the architecture of our training environments for learning spelling and mathematics, and specifically focus on the representation of the conten ...
This contribution introduces an experimental study aiming to provide concrete evidence on how façade and daylight pattern geometry can affect the emotional responses triggered by a space. The study was conducted in Virtual Reality (VR) where participants w ...
Certain brain disorders, resulting from brainstem infarcts, traumatic brain injury, stroke and amyotrophic lateral sclerosis, limit verbal communication despite the patient being fully aware. People that cannot communicate due to neurological disorders wou ...
A new software for modeling pathological speech signals is presented in this paper. The software is called NeuroSpeech. This software enables the analysis of pathological speech signals considering different speech dimensions: phonation, articulation, pros ...
In air traffic control rooms around the world paper flight strips are replaced through different digital solutions. This enables other systems to access the instructed air traffic controller (ATCo) commands and use them for other purposes. Digital flight s ...
This paper explores novel ideas in building end-to-end deep neural network (DNN) based text-dependent speaker verification (SV) system. The baseline approach consists of mapping a variable length speech segment to a fixed dimensional speaker vector by esti ...
Learning a good speaker embedding is critical for many speech processing tasks, including recognition, verification, and diarization. To this end, we propose a complementary optimizing goal called intra-class loss to improve deep speaker embed dings learne ...
We propose a physiologically based intonation model using perceptual relevance. Motivated by speech synthesis from a speech-to-speech translation (S2ST) point of view, we aim at a language independent way of modelling intonation. The model presented in thi ...
