This work presents a novel methodology to train open domain neural dialogue systems within the framework of Generative Adversarial Networks with gradient-based optimization methods. We avoid the non-differentiability related ...

Designing dialogue policies that take user behavior into account is complicated due to user vari- ability and behavioral uncertainty. Attributed Prob- abilistic Finite State Bi-Automata (A-PFSBA) have proven to be a promising ...

User simulation is widely used to generate artificial dialogues in order to train statistical spoken dialogue systems and perform evaluations. This paper presents a neural network approach for user modeling that exploits ...

Machine learning researchers have dealt with the identification of emo- tional cues from speech since it is research domain showing a large number of po- tential applications. Many acoustic parameters have been analyzed ...

The main goal of this work is to provide the cognitive computing community with valuable resources to analyze and simulate the intentionality and/or emotions embedded in the language employed in social media. Specifically, ...

This paper presents a dialogue act taxonomy designed for the development of a conversational agent for elderly. The main goal of this conversational agent is to improve life quality of the user by means of coaching sessions ...

The main goal of this work is to carry out automatic emo-tion detection from speech by using both acoustic and textualinformation. For doing that a set of audios were extracted froma TV show were different guests discuss ...

The EMPATHIC project will research, innovate, explore and validatenew paradigms and platforms, laying the foundation for future generations of Per-sonalised Virtual Coaches to assist elderly people living independently ...

The corrective focus is a particular kind of prosodic prominence where the speaker is intended to correct or to emphasize a concept. This work develops an Artificial Cognitive System (ACS) based on Recurrent ...

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-Human Communication as well as to improve Human- ...