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Modelling and Optimizing on Syntactic N-Grams for Statistical Machine Translation
Rico Sennrich
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Paper Details:
Year: 2015
Venue:
TACL |
Citations
URL
A Joint Dependency Model of Morphological and Syntactic Structure for Statistical Machine Translation
Rico Sennrich
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Barry Haddow
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Bilingual Structured Language Models for Statistical Machine Translation
Ekaterina Garmash
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Christof Monz
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Getting Gender Right in Neural Machine Translation
Eva Vanmassenhove
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Christian Hardmeier
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Andy Way
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Top-down Tree Long Short-Term Memory Networks
Xingxing Zhang
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Liang Lu
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Mirella Lapata
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SuperNMT: Neural Machine Translation with Semantic Supersenses and Syntactic Supertags
Eva Vanmassenhove
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Andy Way
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Edinburgh’s Syntax-Based Systems at WMT 2015
Philip Williams
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Rico Sennrich
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Maria Nadejde
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Matthias Huck
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Philipp Koehn
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Modeling Selectional Preferences of Verbs and Nouns in String-to-Tree Machine Translation
Maria Nădejde
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Alexandra Birch
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Philipp Koehn
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Edinburgh’s Statistical Machine Translation Systems for WMT16
Philip Williams
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Rico Sennrich
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Maria Nădejde
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Matthias Huck
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Barry Haddow
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Ondřej Bojar
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Predicting Target Language CCG Supertags Improves Neural Machine Translation
Maria Nădejde
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Siva Reddy
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Rico Sennrich
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Tomasz Dwojak
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Marcin Junczys-Dowmunt
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Philipp Koehn
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Alexandra Birch
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L1-L2 Parallel Dependency Treebank as Learner Corpus
John Lee
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Keying Li
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Herman Leung
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No URLs Found
Field Of Study
Linguistic Trends
Syntax
Morphology
Task
Syntactic Parsing
Machine Translation
Approach
Deep Learning
Language
Chinese
English
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