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A Differentiable Generative Adversarial Network for Open Domain Dialogue
(2019-04)
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 ...
Can Spontaneous Emotions be Detected from Speech on TV Political Debates?
(IEEE, 2019)
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- ...
Regularized Neural User Model for Goal-Oriented Spoken Dialogue Systems
(Springer, 2018-08-02)
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 ...
Tracking the Expression of Annoyance in Call Centers
(Springer, 2018-08-26)
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 ...
Emotion Detection from Speech and Text
(International Speech Communication Association, 2018-11-21)
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 ...