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Neural machine translation (NMT) becomes a new approach to machine translation and generates much more fluent results compared to statistical machine translation (SMT).
Computing consensus translation from multiple machine translation systems
Srinivas Bangalore, German Bordel, and Giuseppe Richardi. 2001 · 2001
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Statistical multi-source translation
Franz Josef Och and Hermann Ney. 2001 · 2001
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Bleu: a methof for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and WeiJing Zhu. 2002 · 2002
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Minimum bayes-risk decoding for statistical machine translation
Shankar Kumar and William Byrne. 2004 · 2004
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A hierarchical phrase-based model for statistical machine translation
David Chiang. 2005 · 2005
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An empirical study on computing consensus translations from multiple machine translation systems
Wolfgang Macherey and Franz Josef Och. 2007 · 2007
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Improved word-level system combination for machine translation
Antti-Veikko I. Rosti, Spyros Matsoukas, and Richard Schwartz. 2007 · 2007
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Improving alignments for better confusion networks for combining machine translation systems
Necip Fazil Ayan, Jing Zheng, and Wen Wang. 2008 · 2008
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Word reordering alignment for combination of statistical machine translation systems
Maoxi Li and Chengqing Zong. 2008 · 2008
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Incremental hypothesis alignment for building confusion networks with appplication to machine translation systems combination
Antti-Veikko I. Rosti, Bing Zhang, Spyros Matsoukas, and Richard Schwartz. 2008 · 2008
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A comparative study of hypothesis alignment and its improvement for machine translation system combination
Boxing Chen, Min Zhang, Haizhou Li, and Aiti Aw. 2009 · 2009
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Lattice-based system combination for statistical machine translation
Yang Feng, Yang Liu, Haitao Mi, Qun Liu, and Yajuan Lu. 2009 · 2009
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The CASIA statistical machine translation system for IWSLT 2009
Maoxi Li, Jiajun Zhang, Yu Zhou, and Chengqing Zong. 2009 · 2009
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Combining machine translation output with open source
Kenneth Heafield and Alon Lavie. 2010 · 2010
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Automatic evaluation of translation quality for distant language pairs
Hideki Isozaki, Tsutomu Hirao, Kevin Duh, Katsuhito Sudoh, and Hajime Tsukada. 2010 · 2010
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Recurrent continuous translation models
Nal Kalchbrenner and Phil Blunsom. 2013 · 2013
Cited alongside, same era.
Statistical phrase-based translation
Philipp Koehn, Franz J. Och, and Daniel Marcu. 2003 · 2013
Cited alongside, same era.
Learning phrase representations using RNN encoder¨Cdecoder for statistical machine translation
Kyunghyun Cho, Bart van Merrienboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio. 2014 · 2014
Cited alongside, same era.
Jane: open source machine translation system combiantion
Markus Freitag, Matthias Huck, and Hermann Ney. 2014 · 2014
Cited alongside, same era.
Sequence to sequence learning with neural networks
Ilya Sutskever, Oriol Vinyals, and Quoc VV Le. 2014 · 2014
Cited alongside, same era.
Nuural machine translation by jointly learning to align and translate
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2015 · 2015
Is neural machine translation ready for deployment? A case study on 30 translation directions
Marcin Junczys-Dowmunt, Tomasz Dwojak, and Hieu Hoang. 2016a · 2016
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The AMU-UEDIN submission to the WMT16 news translation task: attention-based NMT models as feature functions in phrase-based SMT
Marcin Junczys-Dowmunt, Tomasz Dwojak, and Rico Sennrich. 2016b · 2016
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Towards zero unknown word in neural machine translation
Xiaoqing Li, Jiajun Zhang, and Chengqing Zong. 2016 · 2016
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Interactive attention for neural machine translation
Fandong Meng, Zhengdong Lu, Hang Li, and Qun Liu. 2016 · 2016
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A coverage embedding model for neural machine translation
Haitao Mi, Baskaran Sankaran, Zhiguo Wang, Niyu Ge, and Abe Ittycheriah. 2016a · 2016
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Supervised attentions for neural machine translation
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Effective approaches to attention-based neural machine translation
Minh-Thang Luong, Hieu Pham, and Christopher D. Manning. 2015a · 2015
Cited alongside, same era.
Addressing the rare word problem in neural machine translation
Minh-Thang Luong, Ilya Sutskever, Quoc V Le, Oriol Vinyals, and Wojciech Zaremba. 2015b · 2015
Cited alongside, same era.
System combination for machine translation through paraphrasing
Wei-Yun Ma and Kathleen Mckeown. 2015 · 2015
Cited alongside, same era.
Semi-supervised learning for neural machine translation
Yong Cheng, Wei Xu, Zhongjun He, Wei He, Hua Wu, Maosong Sun, and Yang Liu. 2016 · 2016
Cited alongside, same era.
Multi-way, multilingual neural machine translation with a shared attention mechanism
Orhan Firat, Kyunghyun Cho, and Yoshua Bengio. 2016a · 2016
Cited alongside, same era.
Zero-resource translation with multi-lingual neural machine translation
Orhan Firat, Baskaran Sankaran, Yaser Al-Onaizan, Fatos T. Yarman Vural, and Kyunghyun Cho. 2016b · 2016
Cited alongside, same era.
Haitao Mi, Zhiguo Wang, Niyu Ge, and Abe Ittycheriah. 2016b · 2016
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Pre-translation for neural machine translation
Jan Niehues, Eunah Cho, Thanh-Le Ha, and Alex Waibel. 2016 · 2016
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Improving neural machine translation models with monolingual data
Rico Sennrich, Barry Haddow, and Alexandra Birch. 2016a · 2016
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Neural machine translation of rare words with subword units
Rico Sennrich, Barry Haddow, and Alexandra Birch. 2016b · 2016
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Minimum risk training for neural machine translation
Shiqi Shen, Yong Cheng, Zhongjun He, Wei He, Hua Wu, Maosong Sun, and Yang Liu. 2016 · 2016
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Modeling coverage for neural machine translation
Zhaopeng Tu, Zhengdong Lu, Yang Liu, Xiaohua Liu, and Hang Li. 2016 · 2016
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Exploiting source-side monolingual data in neural machine translation
Jiajun Zhang and Chengqing Zong. 2016b · 2016
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Sentence-level paraphrasing for machine translation system combination
Junguo Zhu, Muyun Yang, Sheng Li, and Tiejun Zhao. 2016 · 2016
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Multi-source neural translation
Barret Zoph and Kevin Knight. 2016 · 2016
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