5 citations · 6 across the 3 of their papers we have counts for
12 papers
Interpretable SincNet-based Deep Learning for Emotion Recognition from EEG brain activity
Juan Manuel Mayor-Torres, Mirco Ravanelli, Sara E. Medina-DeVilliers +2
Machine learning methods, such as deep learning, show promising results in the medical domain. However, the lack of interpretability of these algorithms may hinder their applicabil…
Is this Dialogue Coherent? Learning from Dialogue Acts and Entities
Alessandra Cervone, Giuseppe Riccardi
In this work, we investigate the human perception of coherence in open-domain dialogues. In particular, we address the problem of annotating and modeling the coherence of next-turn…
Annotation of Emotion Carriers in Personal Narratives
Aniruddha Tammewar, Alessandra Cervone, Eva-Maria Messner +1
We are interested in the problem of understanding personal narratives (PN) - spoken or written - recollections of facts, events, and thoughts. In PN, emotion carriers are the speec…
Affective Behaviour Analysis of On-line User Interactions: Are On-line Support Groups more Therapeutic than Twitter?
Giuliano Tortoreto, Evgeny A. Stepanov, Alessandra Cervone +2
The increase in the prevalence of mental health problems has coincided with a growing popularity of health related social networking sites. Regardless of their therapeutic potentia…
Active Annotation: bootstrapping annotation lexicon and guidelines for supervised NLU learning
Federico Marinelli, Alessandra Cervone, Giuliano Tortoreto +3
Natural Language Understanding (NLU) models are typically trained in a supervised learning framework. In the case of intent classification, the predicted labels are predefined and…
An Incremental Turn-Taking Model For Task-Oriented Dialog Systems
Andrei C. Coman, Koichiro Yoshino, Yukitoshi Murase +2
In a human-machine dialog scenario, deciding the appropriate time for the machine to take the turn is an open research problem. In contrast, humans engaged in conversations are abl…