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Reordering Model with Recurrent Neural Networks for Myanmar- English Statistical Machine Translation

http://hdl.handle.net/20.500.12678/0000004997
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6f84143e-e322-47bc-abac-ce41b31457ba
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proceeding_total-pages-441-445.pdf proceeding_total-pages-441-445.pdf (3138 Kb)
Publication type
Article
Upload type
Publication
Title
Title Reordering Model with Recurrent Neural Networks for Myanmar- English Statistical Machine Translation
Language en
Publication date 2017-02-16
Authors
Nyein, May Kyi
Soe, Khin Mar
Description
Word reordering is a problematic issue forlanguage pairs with significantly different word orders,such as the translation between a subject-verb-object(SVO) language and a subject-object-verb (SOV)language. When translating between language pairswith high disparity in word order, reordering isextremely desirable for translation accuracy. In thispaper, the future research directions of reorderingmodels for Myanmar-English statistical machinetranslation (SMT) are also depicted. In this reorderingmodel, the word order on source-side is arranged intothe target side word order, before SMT system isapplied. We propose the use of recurrent neuralnetworks (RNNs) to model preordering for SMT.
Keywords
Reordering, English-Myanmar statistical machine translation, recurrent neural networks
Identifier http://onlineresource.ucsy.edu.mm/handle/123456789/894
Journal articles
Fifteenth International Conference on Computer Applications (ICCA 2017)
Conference papers
Books/reports/chapters
Thesis/dissertations
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