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