High-performance and Lightweight Real-time Deep Face Emotion Recognition

The paper titled “ High-performance and Lightweight Real-time Deep Face Emotion Recognition ” (co-authored by Justus Schwan, Esam Ghaleb, Enrique Hortal and Stylianos Asteriadis) has been accepted for publication at the SMAP2017 – 12th International Workshop on Semantic and Social Media Adaptation and Personalization. This paper will be included as part of the Special Session on Multimodal affective analysis for human-machine interfaces and learning environments.

Personalized, affect and performance-driven Computer-based Learning

Co-authored by C. Athanasiadis, C.Z. Lens, D. Koutsoukos, E. Hortal and S. Asteriadis, the paper entitled "Personalized, affect and performance-driven Computer-based Learning" has been accepted for the 9th International Conference on Computer Supported Education (CSEDU 2017), which will take place in Porto (Portugal) from the 21st to the 23rd of April, 2017.

Recognizing Emotional States using Speech Information

Emotion recognition plays an important role in several applications, such as human computer interaction and understanding afective state of users in certain tasks, e.g., within a learning process, monitoring of elderly, interactive entertainment etc. It may be based upon several modalities, e.g., by analyzing facial expressions and/or speech, using electroencephalograms, electrocardiograms etc. In certain applications the only available modality is the user's (speaker's) voice.