Improving Translation Model by Monolingual Data

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F11%3A10107931" target="_blank" >RIV/00216208:11320/11:10107931 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Improving Translation Model by Monolingual Data
Original language description
We use target-side monolingual data to extend the vocabulary of the translation model in statistical machine translation. This method called "reverse self-training" improves the decoder's ability to produce grammatically correct translations into languages with morphology richer than the source language esp. in small-data setting. We empirically evaluate the gains for several pairs of European languages and discuss some approaches of the underlying back-off techniques needed to translate unseen forms ofknown words. We also provide a description of the systems we submitted to WMT11 Shared Task.
Czech name
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Czech description
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Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the Sixth Workshop on Statistical Machine Translation
ISBN
978-1-937284-12-1
ISSN
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e-ISSN
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Number of pages
7
Pages from-to
330-336
Publisher name
Association for Computational Linguistics
Place of publication
Edinburgh, UK
Event location
Edinburgh, United Kingdom
Event date
Jul 30, 2011
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
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