dc.contributor.author | Núñez Marcos, Adrián | |
dc.contributor.author | Pérez de Viñaspre Garralda, Olatz | |
dc.contributor.author | Labaka Intxauspe, Gorka | |
dc.date.accessioned | 2024-05-21T17:23:45Z | |
dc.date.available | 2024-05-21T17:23:45Z | |
dc.date.issued | 2023-03 | |
dc.identifier.citation | Expert Systems with Applications 213(Part B) : (2023) // Article ID 118993 | es_ES |
dc.identifier.issn | 1873-6793 | |
dc.identifier.issn | 0957-4174 | |
dc.identifier.uri | http://hdl.handle.net/10810/68070 | |
dc.description.abstract | Sign Languages (SLs) are employed by deaf and hard-of-hearing (DHH) people to communicate on a daily basis. However, the communication with hearing people still faces some barriers, mainly because of the scarce knowledge about SLs among hearing people. Hence, tools to allow the communication between users of either sign or spoken languages must be encouraged. A stepping stone in this direction is the research of the sign language translation (SLT) task, which aims to produce a spoken language translation of a sign language video or vice versa. By implementing these types of translators in portable devices, we will make considerable progress towards a barrier-free communication between DHH and hearing people. That is why, in this work, we focus on reviewing the literature on SLT and provide the necessary background about SLs. Besides, we summarise the available datasets and the results found in the literature for one of the most used datasets, the RWTH-PHOENIX-2014T. Moreover, the survey lists the challenges that need to be tackled within the SLT research and also for the adoption of SLT technologies, and proposes future research lines. | es_ES |
dc.description.sponsorship | This work has been conducted within the SignON project. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101017255. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Elsevier | es_ES |
dc.relation | info:eu-repo/grantAgreement/EC/H2020/101017255 | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/es/ | * |
dc.subject | machine learning | es_ES |
dc.subject | sign language translation | es_ES |
dc.subject | sign languages | es_ES |
dc.subject | survey | es_ES |
dc.title | A survey on Sign Language machine translation | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.holder | © 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/) | es_ES |
dc.rights.holder | Atribución 3.0 España | * |
dc.relation.publisherversion | https://www.sciencedirect.com/science/article/pii/S0957417422020115 | es_ES |
dc.identifier.doi | 10.1016/j.eswa.2022.118993 | |
dc.contributor.funder | European Commission | |
dc.departamentoes | Arquitectura y Tecnología de Computadores | es_ES |
dc.departamentoes | Lenguajes y sistemas informáticos | es_ES |
dc.departamentoeu | Hizkuntza eta sistema informatikoak | es_ES |
dc.departamentoeu | Konputagailuen Arkitektura eta Teknologia | es_ES |