Producing Unseen Morphological Variants in Statistical Machine Translation
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F17%3A10372152" target="_blank" >RIV/00216208:11320/17:10372152 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Producing Unseen Morphological Variants in Statistical Machine Translation
Original language description
Translating into morphologically rich languages is difficult. Although the coverage of lemmas may be reasonable, many morphological variants cannot be learned from the training data. We present a statistical translation system that is able to produce these inflected word forms. Different from most previous work, we do not separate morphological prediction from lexical choice into two consecutive steps. Our approach is novel in that it is integrated in decoding and takes advantage of context information from both the source language and the target language sides.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/LM2015071" target="_blank" >LM2015071: Language Research Infrastructure in the Czech Republic</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2017
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 the 15th Conference of the European Chapter of the Association for Computational Linguistics, volume 2: Short Papers
ISBN
978-1-5108-3860-4
ISSN
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e-ISSN
neuvedeno
Number of pages
7
Pages from-to
369-375
Publisher name
Association for Computational Linguistics
Place of publication
Stroudsburg, PA, USA
Event location
Valencia, Spain
Event date
Apr 3, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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