Now showing items 1-5 of 5

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      Characterising the rankings produced by combinatorial optimisation problems and finding their intersections. 

      Hernando Rodríguez, Leticia ORCID; Mendiburu Alberro, Alexander; Lozano Alonso, José Antonio (Association for Computing Machinery, 2019-07)
      [EN] The aim of this paper is to introduce the concept of intersection between combinatorial optimisation problems. We take into account that most algorithms, in their machinery, do not consider the exact objective function ...
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      Mental Health Monitoring from Speech and Language 

      Zubiaga Amar, Irune; Justo Blanco, Raquel ORCID; Menchaca, Ignacio; De Velasco Vázquez, Mikel ORCID (ISCA, 2022)
      Concern for mental health has increased in the last years due to its impact in people life quality and its consequential effect on healthcare systems. Automatic systems that can help in the diagnosis, symptom monitoring, ...
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      Multimodal feature evaluation and fusion for emotional well-being monitorization 

      Zubiaga Amar, Irune; Justo Blanco, Raquel ORCID (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 ...
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      Speech emotion recognition in Spanish TV Debates 

      Zubiaga Amar, Irune; Justo Blanco, Raquel ORCID; De Velasco Vázquez, Mikel ORCID; Torres Barañano, María Inés ORCID (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, ...
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      Transfer learning in hierarchical dialogue topic classification with neural networks 

      Montenegro Portillo, César; Santana Hermida, Roberto ORCID; Lozano Alonso, José Antonio (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 ...