The goal of this work is to automatically analyze the emotional status of speakers, in human-
human interactions, carried out in TV debates, where controversial topics are often …

Decoding emotional states from multimodal signals is an increasingly active domain, within
the framework of affective computing, which aims to a better understanding of Human …

Nowadays, Machine Learning applications are spreading widely in different science and
research fields which gave, in fact, the possibility to enhance the results of all kind of both …

CALLIOPE is a conceptual multi-dimensional model that aims at approximating and
categorizing the prosodic phenomena taking into account of all possible independent factors …

Offering human machine interfaces capable of handling cultural variation in speech is an
exciting topic in cognitive info-communication. From a machine learning point-of-view, this …

Addressing the domain mismatch problem has been a long term interest within cognitive
infocommunication. In particular, several techniques to compensate for dialectal variations of …

Functional Dependency extraction is a useful way to find inherent rules that apply in a given
dataset. However, not all of such rules are exact, datasets comprised of real-world …