CLEAR.TEXT Enhancing the Modernization Public Sector Organizations by Deploying Natural Language Processing to Make Their Digital Content CLEARER to Those with Cognitive Disabilities

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Título: CLEAR.TEXT Enhancing the Modernization Public Sector Organizations by Deploying Natural Language Processing to Make Their Digital Content CLEARER to Those with Cognitive Disabilities
Autor/es: Moreda, Paloma | Botella, Beatriz | Espinosa-Zaragoza, Isabel | Lloret, Elena | Martin, Tania Josephine | Martínez-Barco, Patricio | Suárez Cueto, Armando | Palomar, Manuel
Grupo/s de investigación o GITE: Procesamiento del Lenguaje y Sistemas de Información (GPLSI)
Centro, Departamento o Servicio: Universidad de Alicante. Departamento de Lenguajes y Sistemas Informáticos
Palabras clave: Human Language Technologies | Natural Language Processing | Automatic Text Simplification | Automatic Summaries | Artificial Intelligence
Fecha de publicación: 23-oct-2023
Editor: CEUR
Cita bibliográfica: SEPLN-PD 2023: Annual Conference of the Spanish Association for Natural Language Processing 2023: Projects and System Demonstrations, Jaén, Spain, September 27-29, 2023. CEUR Workshop Proceedings, Vol-3516
Resumen: The CLEAR.TEXT project (TED2021-130707B-I00) researches how natural language processing technology can support the authoring of accessible content in Spanish for people with cognitive disabilities. Our main objective is to research, implement, deploy, evaluate, and ultimately provide robust technologies for natural language processing to support the authoring of accessible Spanish content for public sector organisations (at local, regional and national level) that is intelligible to people with cognitive disability, thereby widening their inclusion and empowerment in Europe. It is expected to impact positively the quality of life of people with cognitive disabilities, facilitating their access to educational, vocational, cultural, and social opportunities in public sector organisations.
Patrocinador/es: This research work is part of the CLEAR.TEXT project (TED2021-130707B-I00), funded by MCIN/AEI/10.13039/501100011033 and European Union NextGenerationEU/PRTR.
URI: http://hdl.handle.net/10045/138197
ISSN: 1613-0073
Idioma: eng
Tipo: info:eu-repo/semantics/conferenceObject
Derechos: © 2023 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
Revisión científica: si
Versión del editor: https://ceur-ws.org/Vol-3516/
Aparece en las colecciones:INV - GPLSI - Comunicaciones a Congresos, Conferencias, etc.

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