DC FieldValueLanguage
dc.contributor.authorNtalianis, Klimis-
dc.contributor.authorKouremenos, Dimitris-
dc.contributor.authorSiolas, Georgios-
dc.contributor.authorStafylopatis, Andreas-
dc.date.accessioned2024-10-29T14:17:01Z-
dc.date.available2024-10-29T14:17:01Z-
dc.date.issued2018-01-01-
dc.identifierscopus-85057797842-
dc.identifier.issn1613-0073-
dc.identifier.other85057797842-
dc.identifier.urihttps://uniwacris.uniwa.gr/handle/3000/2849-
dc.description.abstractOne of the objectives of Assistive Technologies is to help people with disabilities communicate with others and provide means of access to information. As an aid to Deaf people, we present in this work a novel prototype Rule-Based Machine Translation (RBMT) system for the creation of large quality written Greek text to Greek Sign Language (GSL) glossed corpora. In particular, the proposed RBMT system supports the professional translator of GSL to produce high quality parallel Greek text - GSL glossed corpus, which is then used as training data by the Statistical Machine Translation (SMT) MOSES [1] application system. It should be noted that the whole process is robust and flexible, since it does not demand deep grammar knowledge of GSL. With this work we manage to overcome the two biggest obstacles in Natural Processing Language (NLP) of GSL. Firstly, the lack of written system and secondly the lack of grammar and finally we have been able to lay the foundations for an autonomous translation system of Greek text to GSL. Evaluation of the proposed scheme is carried out in the weather reports domain, where 20,284 tokens and 1,000 sentences have been produced. By using the BiLingual Evaluation Understudy (BLEU) metric score, our prototyped MT system achieves a relative average score of 60.53% and 85.1%/65.5%/53.8%/44.8% for for 1-gram/2-gram/3-gram/4-gram evaluation.en_US
dc.language.isoenen_US
dc.relation.ispartofCEUR Workshop Proceedingsen_US
dc.subjectDeaf people communicationen_US
dc.subjectGreeken_US
dc.subjectGreek Sign Languageen_US
dc.subjectGSLen_US
dc.subjectMachine translationen_US
dc.subjectMosesen_US
dc.subjectPhrase modelen_US
dc.subjectSMTen_US
dc.titleStatistical machine translation for Greek to Greek sign language using parallel corpora produced via rule-based machine translationen_US
dc.typeConference Paperen_US
dc.relation.conference8th International Workshop on Combinations of Intelligent Methods and Applications (CIMA 2018), 7 November 2018, Volos, Greeceen_US
dc.identifier.scopus2-s2.0-85057797842-
dcterms.accessRights0en_US
dc.relation.deptDepartment of Business Administrationen_US
dc.relation.facultySchool of Administrative, Economics and Social Sciencesen_US
dc.relation.volume2252en_US
dc.identifier.spage28en_US
dc.identifier.epage42en_US
dc.linkhttps://ceur-ws.org/Vol-2252/en_US
dc.collaborationUniversity of West Attica (UNIWA)en_US
dc.journalsOpen Accessen_US
dc.publicationPeer Revieweden_US
dc.countryGreeceen_US
local.metadatastatusnot verifieden_US
item.fulltextNo Fulltext-
item.grantfulltextnone-
item.openairetypeConference Paper-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
crisitem.author.deptDepartment of Business Administration-
crisitem.author.facultySchool of Administrative, Economics and Social Sciences-
crisitem.author.parentorgSchool of Administrative, Economics and Social Sciences-
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