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System architecture and deployment scenarios for SESAME: Small cEllS coordinAtion for Multi-tenancy and Edge services
(2016-05-17)
The surge of the Internet traffic with exabytes of data flowing over operators mobile networks has created the need to rethink the paradigms behind the design of the mobile network architecture. The inadequacy of the 4G ...
Building synthetic simulated environments for configuring and training multi-camera systems for surveillance applications
(SciTePress, Science and Technology Publications, Lda, 2021)
[EN] Synthetic simulated environments are gaining popularity in the Deep Learning Era, as they can alleviate the
effort and cost of two critical tasks to build multi-camera systems for surveillance applications: setting ...
Transfer learning in hierarchical dialogue topic classification with neural networks
(IEEE, 2020-09-28)
Knowledge transfer between tasks can significantly improve the efficiency of machine learning algorithms. In supervised natural language understanding problems, this sort of improvement is critical since the availability ...
LSTM based voice conversion for laryngectomees
(International Speech Communication Association, 2018-11-23)
This paper describes a voice conversion system designed withthe aim of improving the intelligibility and pleasantness of oe-sophageal voices. Two different systems have been built, oneto transform the spectral magnitude ...
Listening to Laryngectomees: A study of Intelligibility and Self-reportedListening Effort of Spanish Oesophageal Speech
(International Speech Communication Association, 2018-11-23)
Oesophageal speakers face a multitude of challenges, such asdifficulty in basic everyday communication and inability to in-teract with digital voice assistants. We aim to quantify the diffi-culty involved in understanding ...
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- ...
Speech emotion recognition in Spanish TV Debates
(ISCA, 2022)
Emotion recognition from speech is an active field of study that can help build more natural human-machine interaction systems. Even though the advancement of deep learning technology has brought improvements in this task, ...
Multimodal feature evaluation and fusion for emotional well-being monitorization
(Springer, 2022-04-26)
Mental health is a global issue that plays an important roll in the overall well-being of a person. Because of this, it is important to preserve it, and conversational systems have proven to be helpful in this task. This ...
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 ...