Examinar Comunicaciones por departamento (eus.) "Elektrizitatea eta elektronika"

A Differentiable Generative Adversarial Network for Open Domain Dialogue

López Zorrilla, Asier

; De Velasco Vázquez, Mikel

; Torres Barañano, María Inés

(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 ...

A Hardware/Software Extreme Learning Machine Solution for Improved Ride Comfort in Automobiles

Mata Carballeira, Oscar

; Del Campo Hagelstrom, Inés Juliana

; Martínez González, María Victoria (IEEE, 2019-09-30)

Automotive ride comfort has become an important research topic in recent years due to the increasing level of automation in currently produced cars. These premises also apply to manned cars. In this work, a hybrid ...

A Spanish Corpus for Talking to the Elderly

Justo Blanco, Raquel

; Ben Letaifa Zouari, Leila; Olaso Fernández, Javier Mikel; López Zorrilla, Asier

; De Velasco Vázquez, Mikel

; Vázquez Risco, Alain; Torres Barañano, María Inés

(Springer, 2020-10-25)

In this work, a Spanish corpus that was developed, within the EMPATHIC project (http://www.empathic-project.eu/) framework, is presented. It was designed for building a dialogue system capable of talking to elderly people ...

Adding dimensional features for emotion recognition on speech

Ben Letaifa Zouari, Leila; Torres Barañano, María Inés

; Justo Blanco, Raquel

(IEEE, 2020-10-20)

Developing accurate emotion recognition systems requires extracting suitable features of these emotions. In this paper, we propose an original approach of parameters extraction based on the strong, theoretical and empirical, ...

Approximate Best Proximity Points of Cyclic Self-maps in Metric Spaces and Cyclic Asymptotic Regularity

De la Sen Parte, Manuel

(IOP Publishing, 2015)

This manuscript investigates some relations and properties between 2-cyclic self-mappings. In particular, a formal development is given to link some concepts and their basic related properties like those of approximate ...

Audio Embeddings help to learn better dialogue policies

López Zorrilla, Asier

; Torres Barañano, María Inés

; Cuayáhuitl, Heriberto (IEEE, 2021-12)

Neural transformer architectures have gained a lot of interest for text-based dialogue management in the last few years. They have shown high learning capabilities for open domain dialogue with huge amounts of data and ...

Batch-level GANs to promote dialogue response variety

López Zorrilla, Asier

; Vázquez Risco, Alain; Torres Barañano, María Inés

(2023-02-24)

Exploiting large pretrained transformers has become one of the most popular approaches for dialogue modelling. Nonetheless, due to their lack of robustness and explainability, we believe it is necessary to keep exploring ...

Can Spontaneous Emotions be Detected from Speech on TV Political Debates?

De Velasco Vázquez, Mikel

; Justo Blanco, Raquel

; López Zorrilla, Asier

; Torres Barañano, María Inés

(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- ...

Contrasting the Emotions identified in Spanish TV debates and in Human-Machine Interactions

De Velasco Vázquez, Mikel

; Justo Blanco, Raquel

; Ben Letaifa Zouari, Leila; Torres Barañano, María Inés

(ISCA, 2020-03-24)

This work is aimed to contrast the similarities and differences for the emotions identified in two very different scenarios: human-to-human interaction on Spanish TV debates and human-machine interaction with a virtual ...

Deep Extreme Learning Machines with Auto Encoder for Speed Limit Signs Recognition

Mata Carballeira, Oscar

; Del Campo Hagelstrom, Inés Juliana

; Martínez González, María Victoria; Echanove Arias, Francisco Javier

(IEEE, 2018-12-09)

This work presents a Deep Extreme Learning Machine with Auto Encoder scheme for Speed Limit Signs Recognition in the field of Advanced Driving Assistance Systems, where traffic sign recognition from video imaging plays an ...

Defects structure characterization of NiMnGa alloys by PALS

Mérida Sanz, David; García Martínez, José Angel; Plazaola Muguruza, Fernando; Sánchez Alarcos, Vicente; Pérez Landazbal, Jose Ignacio; Recarte, Vicente (IOP Publishing, 2013)

We have studied the behaviour of defects in off-stoichiometric Ni-Mn-Ga ferromagnetic shape memory alloys by means of positron lifetime spectroscopy. The measurements presented in this work have been performed in six ternary ...

Detecting Critical Resonances in Microwave Amplifiers through Noise Simulations

Collantes Metola, Juan María

; Otegi Urdanpilleta, Nerea

; Anakabe Iturriaga, Aitziber; Mori Carrascal, Libe; Barcenilla Irazu, Asier; Gónzalez Pérez, José Manuel (IEEE, 2019-04-29)

The presence of critical resonances in microwave power amplifiers has a negative impact on its behavior and performance. These critical resonances are usually predicted from pole-zero stability simulations. In this paper, ...

Driving Style Recognition based on Ride Comfort Using a Hybrid Machine Learning Algorithm

Del Campo Hagelstrom, Inés Juliana

; Asua Uriarte, Estibaliz

; Martínez González, María Victoria; Mata Carballeira, Oscar

; Echanove Arias, Francisco Javier

(IEEE, 2018-12-09)

Driving style (DS) classification and identification plays an increasingly important role in the development of advanced driver assistance systems and automated vehicles. Both the enhancement of driving safety and the ...

Emotion Detection from Speech and Text

De Velasco Vázquez, Mikel

; Justo Blanco, Raquel

; Antón, Josu; Carrilero, Mikel; Torres Barañano, María Inés

(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 ...

Euskaraz hitz egiten ikasten duten makina autodidaktak

López Zorrilla, Asier

; De Velasco Vázquez, Mikel

; Justo Blanco, Raquel

(Udako Euskal Unibertsitatea, 2019-05)

Lan honetan sare neuronalen bidez euskaraz hitz egiten ikasten duen elkarrizketa sistema automatikoa aurkezten dugu. Horretarako, Turingen testaren ideia era konputazionalean inplementatzen duten sare neuronal sortzaile ...

First Steps to Develop a Corpus of Interactions between Elderly and Virtual Agents in Spanish with Emotion Labels

Ben Letaifa Zouari, Leila; De Velasco Vázquez, Mikel

; Justo Blanco, Raquel

; Torres Barañano, María Inés

(SLSP 2019, 2019-10)

...

Iruzurrezko portaeren detekzioa crowd motako etiketazioan

De Velasco Vázquez, Mikel

; López Zorrilla, Asier

; Justo Blanco, Raquel

(Udako Euskal Unibertsitatea, 2019-05)

This work aims at detecting low quality labels in crowdsourcing annotation tasks. We validate our proposal carrying out experiments in a difficult and subjective task: emotion recognition. We have developed several measures ...

Knowledge-grounded dialogue act transfer using prompt-based learning for controllable open-domain NLG

Vázquez Risco, Alain; Ramírez, Angela María; Pullabhotla, Neha; Qiang, Nan; Zhang, Haoran; Walker, Marilyn; Torres Barañano, María Inés

(Association for Computational Linguistics, 2024-09)

Open domain spoken dialogue systems need to controllably generate many different dialogue acts (DAs) to allow Natural Language Generation (NLG) to create interesting and engaging conversational interactions with users. We ...

SPIN at MentalRiskES 2023: Transformer-Based Model for Real-Life Depression Detection in Messaging Apps

Zubiaga Amar, Irune; Justo Blanco, Raquel

(CEUR-WS, 2023)

Depression is a prevalent and severe mental health condition that significantly impacts global population, causing personal suffering and reduced quality of life. Its symptoms are often visible on social media and digital ...