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Statements

Subject Item
n2:RIV%2F00216208%3A11320%2F12%3A10130091%21RIV13-GA0-11320___
rdf:type
n16:Vysledek skos:Concept
rdfs:seeAlso
http://www.aclweb.org/anthology-new/W/W12/W12-4205.pdf
dcterms:description
In this paper, we present two dependency parser training methods appropriate for parsing outputs of statistical machine translation (SMT), which pose problems to standard parsers due to their frequent ungrammaticality. We adapt the MST parser by exploiting additional features from the source language, and by introducing artificial grammatical errors in the parser training data, so that the training sentences resemble SMT output. We evaluate the modified parser on DEPFIX, a system that improves English-Czech SMT outputs using automatic rule-based corrections of grammatical mistakes which requires parsed SMT output sentences as its input. Both parser modifications led to improvements in BLEU score; their combination was evaluated manually, showing a statistically significant improvement of the translation quality. In this paper, we present two dependency parser training methods appropriate for parsing outputs of statistical machine translation (SMT), which pose problems to standard parsers due to their frequent ungrammaticality. We adapt the MST parser by exploiting additional features from the source language, and by introducing artificial grammatical errors in the parser training data, so that the training sentences resemble SMT output. We evaluate the modified parser on DEPFIX, a system that improves English-Czech SMT outputs using automatic rule-based corrections of grammatical mistakes which requires parsed SMT output sentences as its input. Both parser modifications led to improvements in BLEU score; their combination was evaluated manually, showing a statistically significant improvement of the translation quality.
dcterms:title
Using Parallel Features in Parsing of Machine-Translated Sentences for Correction of Grammatical Errors Using Parallel Features in Parsing of Machine-Translated Sentences for Correction of Grammatical Errors
skos:prefLabel
Using Parallel Features in Parsing of Machine-Translated Sentences for Correction of Grammatical Errors Using Parallel Features in Parsing of Machine-Translated Sentences for Correction of Grammatical Errors
skos:notation
RIV/00216208:11320/12:10130091!RIV13-GA0-11320___
n16:predkladatel
n17:orjk%3A11320
n3:aktivita
n4:P n4:S
n3:aktivity
P(GD201/09/H057), S
n3:dodaniDat
n14:2013
n3:domaciTvurceVysledku
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n10:D
n3:duvernostUdaju
n20:S
n3:entitaPredkladatele
n9:predkladatel
n3:idSjednocenehoVysledku
176547
n3:idVysledku
RIV/00216208:11320/12:10130091
n3:jazykVysledku
n12:eng
n3:klicovaSlova
errors; grammatical; correction; sentences; translated; machine; parsing; features; parallel; using
n3:klicoveSlovo
n8:parallel n8:sentences n8:errors n8:translated n8:grammatical n8:machine n8:features n8:using n8:parsing n8:correction
n3:kontrolniKodProRIV
[124298361B9A]
n3:mistoKonaniAkce
Jeju, Korea
n3:mistoVydani
Jeju, Korea
n3:nazevZdroje
Proceedings of Sixth Workshop on Syntax, Semantics and Structure in Statistical Translation (SSST-6), ACL
n3:obor
n18:IN
n3:pocetDomacichTvurcuVysledku
4
n3:pocetTvurcuVysledku
4
n3:projekt
n13:GD201%2F09%2FH057
n3:rokUplatneniVysledku
n14:2012
n3:tvurceVysledku
Dušek, Ondřej Popel, Martin Rosa, Rudolf Mareček, David
n3:typAkce
n21:CST
n3:zahajeniAkce
2012-07-12+02:00
s:numberOfPages
10
n15:hasPublisher
Association for Computational Linguistics
n23:isbn
978-1-937284-38-1
n22:organizacniJednotka
11320