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Statements

Subject Item
n2:RIV%2F00216208%3A11320%2F12%3A10130024%21RIV13-GA0-11320___
rdf:type
skos:Concept n13:Vysledek
dcterms:description
In recent years, machine translation (MT) research has focused on investigating how hybrid machine translation as well as system combination approaches can be designed so that the resulting hybrid translations show an improvement over the individual %22component%22 translations. As a first step towards achieving this objective we have developed a parallel corpus with source text and the corresponding translation output from a number of machine translation engines, annotated with metadata information, capturing aspects of the translation process performed by the different MT systems. This corpus aims to serve as a basic resource for further research on whether hybrid machine translation algorithms and system combination techniques can benefit from additional (linguistically motivated, decoding, and runtime) information provided by the different systems involved. In this paper, we describe the annotated corpus we have created. We provide an overview on the component MT systems and the XLIFF-based annotation f In recent years, machine translation (MT) research has focused on investigating how hybrid machine translation as well as system combination approaches can be designed so that the resulting hybrid translations show an improvement over the individual %22component%22 translations. As a first step towards achieving this objective we have developed a parallel corpus with source text and the corresponding translation output from a number of machine translation engines, annotated with metadata information, capturing aspects of the translation process performed by the different MT systems. This corpus aims to serve as a basic resource for further research on whether hybrid machine translation algorithms and system combination techniques can benefit from additional (linguistically motivated, decoding, and runtime) information provided by the different systems involved. In this paper, we describe the annotated corpus we have created. We provide an overview on the component MT systems and the XLIFF-based annotation f
dcterms:title
A Richly Annotated, Multilingual Parallel Corpus for Hybrid Machine Translation A Richly Annotated, Multilingual Parallel Corpus for Hybrid Machine Translation
skos:prefLabel
A Richly Annotated, Multilingual Parallel Corpus for Hybrid Machine Translation A Richly Annotated, Multilingual Parallel Corpus for Hybrid Machine Translation
skos:notation
RIV/00216208:11320/12:10130024!RIV13-GA0-11320___
n13:predkladatel
n14:orjk%3A11320
n4:aktivita
n16:P
n4:aktivity
P(GBP103/12/G084)
n4:dodaniDat
n6:2013
n4:domaciTvurceVysledku
n22:2787865
n4:druhVysledku
n19:D
n4:duvernostUdaju
n10:S
n4:entitaPredkladatele
n20:predkladatel
n4:idSjednocenehoVysledku
120573
n4:idVysledku
RIV/00216208:11320/12:10130024
n4:jazykVysledku
n21:eng
n4:klicovaSlova
translation; machine; hybrid; corpus; parallel; multilingual; annotated; richly
n4:klicoveSlovo
n5:richly n5:hybrid n5:machine n5:translation n5:parallel n5:corpus n5:multilingual n5:annotated
n4:kontrolniKodProRIV
[C140EC7397F2]
n4:mistoKonaniAkce
İstanbul, Turkey
n4:mistoVydani
İstanbul, Turkey
n4:nazevZdroje
Proceedings of the 8th International Conference on Language Resources and Evaluation (LREC 2012)
n4:obor
n17:IN
n4:pocetDomacichTvurcuVysledku
1
n4:pocetTvurcuVysledku
5
n4:projekt
n9:GBP103%2F12%2FG084
n4:rokUplatneniVysledku
n6:2012
n4:tvurceVysledku
Pecina, Pavel Costa-Jussa, Marta R. Federmann, Christian Avramidis, Eleftherios van Genabith, Josef
n4:typAkce
n8:CST
n4:zahajeniAkce
2012-05-21+02:00
s:numberOfPages
5
n11:hasPublisher
European Language Resources Association
n12:isbn
978-2-9517408-7-7
n18:organizacniJednotka
11320