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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. (en)
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 (en)
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 (en)
skos:notation
  • RIV/00216208:11320/12:10130091!RIV13-GA0-11320___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GD201/09/H057), S
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 176547
http://linked.open...ai/riv/idVysledku
  • RIV/00216208:11320/12:10130091
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • errors; grammatical; correction; sentences; translated; machine; parsing; features; parallel; using (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [124298361B9A]
http://linked.open...v/mistoKonaniAkce
  • Jeju, Korea
http://linked.open...i/riv/mistoVydani
  • Jeju, Korea
http://linked.open...i/riv/nazevZdroje
  • Proceedings of Sixth Workshop on Syntax, Semantics and Structure in Statistical Translation (SSST-6), ACL
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Mareček, David
  • Popel, Martin
  • Dušek, Ondřej
  • Rosa, Rudolf
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • Association for Computational Linguistics
https://schema.org/isbn
  • 978-1-937284-38-1
http://localhost/t...ganizacniJednotka
  • 11320
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