Multimodal machine learning (MML) is a tempting multidisciplinary research area where
heterogeneous data from multiple modalities and machine learning (ML) are combined to …

Emotion detection has become one of the most important aspects to consider in any project
related to Affective Computing. Due to the almost endless applications of this new discipline …

Digital monitoring of physiological signals can allow computer systems to adapt
unobtrusively to users, so as to enhance personalised 'smart'interactions. In recent years …

The TARDIS project aims to build a scenario-based serious-game simulation platform for
NEETs and job-inclusion associations that supports social training and coaching in the …

Automatic detection and interpretation of social signals carried by voice, gestures, mimics,
etc. will play a key-role for next-generation interfaces as it paves the way towards a more …

This paper introduces the Visual Inspection Tool (VIT) which supports researchers in the
annotation of multimodal data as well as the processing and exploitation for learning …

There is an increasing interest in Multimodal Learning Analytics (MMLA), which involves
complex technical issues in gathering, merging and analyzing different types of learning …

During face-to-face interactions, people naturally integrate nonverbal behaviors such as
facial expressions and body postures as part of the conversation to infer the communicative …

This paper presents the voice emotion recognition part of the FILTWAM framework for real-
time emotion recognition in affective e-learning settings. FILTWAM (Framework for Improving …

In this paper we present a complete interactive system enabled to detect human laughs and
respond appropriately, by integrating the information of the human behavior and the context …