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Assessing an application of spontaneous stressed speech - emotions portal

  • Autores: Daniel Palacios Alonso Árbol académico, Carlos A. Lázaro Carrascosa, Agustín López, Guillermo Meléndez, Andrés Gómez Rodellar, Andrés Loor, Victor Nieto Lluis Árbol académico, V. Rodellar Biarge Árbol académico, Athanasios Tsanas, Pedro Gómez Vilda Árbol académico
  • Localización: Understanding the Brain Function and Emotions: 8th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2019 Almería, Spain, June 3–7, 2019 Proceedings, Part I / José Manuel Ferrández Vicente (dir. congr.) Árbol académico, José Ramón Álvarez Sánchez (dir. congr.) Árbol académico, Félix de la Paz López (dir. congr.) Árbol académico, Francisco Javier Toledo Moreo (dir. congr.), Hojjat Adeli (dir. congr.), 2019, ISBN 978-3-030-19591-5, págs. 149-160
  • Idioma: inglés
  • Texto completo no disponible (Saber más ...)
  • Resumen
    • Detecting and identifying emotions expressed in speech signals is a very complex task that generally requires processing a largesample size to extract intricate details and match the diversity of human expression in speech. There is not an emotional dataset commonly accepted as a standard test bench to evaluate the performance of the supervised machine learning algorithms when presented with extracted speech characteristics. This work proposes a generic platform to capture and validate emotional speech.The aim of the platform is collaborativecrowdsourcing and it can be used for any language (currently, it is available in four languages such as Spanish, English, German and French).As an example, a module for elicitation of stress in speech through a set of online interviews and other module for labeling recorded speech have been developed.This study is envisaged as the beginning of an effort to establish a large, cost-free standard speech corpus to assess emotions across multiple languages.


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