Using Parallel Features in Parsing of Machine-Translated Sentences for Correction of Grammatical Errors
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F12%3A10130091" target="_blank" >RIV/00216208:11320/12:10130091 - isvavai.cz</a>
Result on the web
<a href="http://www.aclweb.org/anthology-new/W/W12/W12-4205.pdf" target="_blank" >http://www.aclweb.org/anthology-new/W/W12/W12-4205.pdf</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Using Parallel Features in Parsing of Machine-Translated Sentences for Correction of Grammatical Errors
Original language 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.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
<a href="/en/project/GD201%2F09%2FH057" target="_blank" >GD201/09/H057: Res Informatica</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of Sixth Workshop on Syntax, Semantics and Structure in Statistical Translation (SSST-6), ACL
ISBN
978-1-937284-38-1
ISSN
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e-ISSN
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Number of pages
10
Pages from-to
39-48
Publisher name
Association for Computational Linguistics
Place of publication
Jeju, Korea
Event location
Jeju, Korea
Event date
Jul 12, 2012
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
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