Conference paper Open Access
Ngo, Thi-Vinh; Ha, Thanh-Le; Nguyen, Phuong-Thai; Nguyen, Le-Minh
<?xml version='1.0' encoding='utf-8'?> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:adms="http://www.w3.org/ns/adms#" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dct="http://purl.org/dc/terms/" xmlns:dctype="http://purl.org/dc/dcmitype/" xmlns:dcat="http://www.w3.org/ns/dcat#" xmlns:duv="http://www.w3.org/ns/duv#" xmlns:foaf="http://xmlns.com/foaf/0.1/" xmlns:frapo="http://purl.org/cerif/frapo/" xmlns:geo="http://www.w3.org/2003/01/geo/wgs84_pos#" xmlns:gsp="http://www.opengis.net/ont/geosparql#" xmlns:locn="http://www.w3.org/ns/locn#" xmlns:org="http://www.w3.org/ns/org#" xmlns:owl="http://www.w3.org/2002/07/owl#" xmlns:prov="http://www.w3.org/ns/prov#" xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#" xmlns:schema="http://schema.org/" xmlns:skos="http://www.w3.org/2004/02/skos/core#" xmlns:vcard="http://www.w3.org/2006/vcard/ns#" xmlns:wdrs="http://www.w3.org/2007/05/powder-s#"> <rdf:Description rdf:about="https://doi.org/10.5281/zenodo.3525490"> <rdf:type rdf:resource="http://www.w3.org/ns/dcat#Dataset"/> <dct:type rdf:resource="http://purl.org/dc/dcmitype/Text"/> <dct:identifier rdf:datatype="http://www.w3.org/2001/XMLSchema#anyURI">https://doi.org/10.5281/zenodo.3525490</dct:identifier> <foaf:page rdf:resource="https://doi.org/10.5281/zenodo.3525490"/> <dct:creator> <rdf:Description> <rdf:type rdf:resource="http://xmlns.com/foaf/0.1/Agent"/> <foaf:name>Ngo, Thi-Vinh</foaf:name> <foaf:givenName>Thi-Vinh</foaf:givenName> <foaf:familyName>Ngo</foaf:familyName> <org:memberOf> <foaf:Organization> <foaf:name>University of Information and Communication Technology, TNU, Vietnam</foaf:name> </foaf:Organization> </org:memberOf> </rdf:Description> </dct:creator> <dct:creator> <rdf:Description> <rdf:type rdf:resource="http://xmlns.com/foaf/0.1/Agent"/> <foaf:name>Ha, Thanh-Le</foaf:name> <foaf:givenName>Thanh-Le</foaf:givenName> <foaf:familyName>Ha</foaf:familyName> <org:memberOf> <foaf:Organization> <foaf:name>Institute of Anthropomatics and Robotics, KIT, Germany</foaf:name> </foaf:Organization> </org:memberOf> </rdf:Description> </dct:creator> <dct:creator> <rdf:Description> <rdf:type rdf:resource="http://xmlns.com/foaf/0.1/Agent"/> <foaf:name>Nguyen, Phuong-Thai</foaf:name> <foaf:givenName>Phuong-Thai</foaf:givenName> <foaf:familyName>Nguyen</foaf:familyName> <org:memberOf> <foaf:Organization> <foaf:name>University of Engineering and Technology, VNU, Vietnam</foaf:name> </foaf:Organization> </org:memberOf> </rdf:Description> </dct:creator> <dct:creator> <rdf:Description> <rdf:type rdf:resource="http://xmlns.com/foaf/0.1/Agent"/> <foaf:name>Nguyen, Le-Minh</foaf:name> <foaf:givenName>Le-Minh</foaf:givenName> <foaf:familyName>Nguyen</foaf:familyName> <org:memberOf> <foaf:Organization> <foaf:name>School of Information Science, JAIST, Japan</foaf:name> </foaf:Organization> </org:memberOf> </rdf:Description> </dct:creator> <dct:title>How Transformer Revitalizes Character-based Neural Machine Translation: An Investigation on Japanese-Vietnamese Translation Systems</dct:title> <dct:publisher> <foaf:Agent> <foaf:name>Zenodo</foaf:name> </foaf:Agent> </dct:publisher> <dct:issued rdf:datatype="http://www.w3.org/2001/XMLSchema#gYear">2019</dct:issued> <dct:issued rdf:datatype="http://www.w3.org/2001/XMLSchema#date">2019-11-02</dct:issued> <dct:language rdf:resource="http://publications.europa.eu/resource/authority/language/ENG"/> <owl:sameAs rdf:resource="https://zenodo.org/record/3525490"/> <adms:identifier> <adms:Identifier> <skos:notation rdf:datatype="http://www.w3.org/2001/XMLSchema#anyURI">https://zenodo.org/record/3525490</skos:notation> <adms:schemeAgency>url</adms:schemeAgency> </adms:Identifier> </adms:identifier> <dct:isVersionOf rdf:resource="https://doi.org/10.5281/zenodo.3525489"/> <dct:isPartOf rdf:resource="https://zenodo.org/communities/iwslt2019"/> <dct:description><p>While translating between East Asian languages, many works have discovered clear advantages of using characters as the translation unit. Unfortunately, traditional recurrent neural machine translation systems hinder the practical usage of those character-based systems due to their architectural limitations. They are unfavorable in handling extremely long sequences as well as highly restricted in parallelizing the computations. In this paper, we demonstrate that the new transformer architecture can perform character-based trans- lation better than the recurrent one. We conduct experiments on a low-resource language pair: Japanese-Vietnamese. Our models considerably outperform the state-of-the-art systems which employ word-based recurrent architectures.</p></dct:description> <dct:accessRights rdf:resource="http://publications.europa.eu/resource/authority/access-right/PUBLIC"/> <dct:accessRights> <dct:RightsStatement rdf:about="info:eu-repo/semantics/openAccess"> <rdfs:label>Open Access</rdfs:label> </dct:RightsStatement> </dct:accessRights> <dcat:distribution> <dcat:Distribution> <dct:license rdf:resource="https://creativecommons.org/licenses/by/4.0/legalcode"/> <dcat:accessURL rdf:resource="https://doi.org/10.5281/zenodo.3525490"/> </dcat:Distribution> </dcat:distribution> <dcat:distribution> <dcat:Distribution> <dcat:accessURL>https://doi.org/10.5281/zenodo.3525490</dcat:accessURL> <dcat:byteSize>266465</dcat:byteSize> <dcat:downloadURL>https://zenodo.org/record/3525490/files/IWSLT2019_paper_28.pdf</dcat:downloadURL> <dcat:mediaType>application/pdf</dcat:mediaType> </dcat:Distribution> </dcat:distribution> </rdf:Description> </rdf:RDF>
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