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The quality of neural machine translation can be improved by leveraging additional monolingual resources to create synthetic training data.
Translationese in machine translation evaluation
Yvette Graham, Barry Haddow, and Philipp Koehn. 2019 · 1906
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The measurement of observer agreement for categorical data
J. Richard Landis and Gary G. Koch. 1977 · 1977
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Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002 · 2002
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A New Approach to the Study of Translationese: Machine-learning the Difference between Original and Translated Text
Marco Baroni and Silvia Bernardini. 2005 · 2005
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Large language models in machine translation
Thorsten Brants, Ashok C. Popat, Peng Xu, Franz J. Och, and Jeffrey Dean. 2007 · 2007
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(meta-) evaluation of machine translation
Chris Callison-Burch, Cameron Fordyce, Philipp Koehn, Christof Monz, and Josh Schroeder. 2007 · 2007
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Semi-supervised model adaptation for statistical machine translation
Nicola Ueffing, Gholamreza Haffari, and Anoop Sarkar. 2007 · 2007
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Domain adaptation for statistical machine translation with monolingual resources
Nicola Bertoldi and Marcello Federico. 2009 · 2009
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One-Way ANOVA , pages 165–191. Springer New York, New York, NY
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Automatic detection of translated text and its impact on machine translation
David Kurokawa, Cyril Goutte, and Pierre Isabelle. 2009 · 2009
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Identification of translationese: A machine learning approach
Iustina Ilisei, Diana Inkpen, Gloria Corpas Pastor, and Ruslan Mitkov. 2010 · 2010
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Improving translation model by monolingual data
Ondřej Bojar and Aleš Tamchyna. 2011 · 2011
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Translationese and its dialects
Moshe Koppel and Noam Ordan. 2011 · 2011
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Investigations on Translation Model Adaptation Using Monolingual Data
Patrik Lambert, Holger Schwenk, Christophe Servan, and Sadaf Abdul-Rauf. 2011 · 2011
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Adapting translation models to translationese improves SMT
Gennadi Lembersky, Noam Ordan, and Shuly Wintner. 2012 · 2012
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Neural machine translation by jointly learning to align and translate
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2015 · 2015
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Findings of the 2015 workshop on statistical machine translation
Ondrej Bojar, Rajen Chatterjee, Christian Federmann, Barry Haddow, Matthias Huck, Chris Hokamp, Philipp Koehn, Varvara Logacheva, Christof Monz, Matteo Negri, Matt Post, Carolina Scarton, Lucia Specia, and Marco Turchi. 2015 · 2015
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Unsupervised identification of translationese
Ella Rabinovich and Shuly Wintner. 2015 · 2015
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Interpretese vs. translationese: The uniqueness of human strategies in simultaneous interpretation
He He, Jordan Boyd-Graber, and Hal Daumé III. 2016 · 2016
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Sequence-Level Knowledge Distillation
Yoon Kim and Alexander M. Rush. 2016 · 2016
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Findings of the 2019 conference on machine translation (WMT19)
Loïc Barrault, Ondřej Bojar, Marta R. Costa-jussà, Christian Federmann, Mark Fishel, Yvette Graham, Barry Haddow, Matthias Huck, Philipp Koehn, Shervin Malmasi, Christof Monz, Mathias Müller, Santanu Pal, Matt Post, and Marcos Zampieri. 2019 · 2019
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Tagged back-translation
Isaac Caswell, Ciprian Chelba, and David Grangier. 2019 · 2019
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On the evaluation of machine translation systems trained with back-translation
Sergey Edunov, Myle Ott, Marc’Aurelio Ranzato, and Michael Auli. 2019 · 2019
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APE at scale and its implications on MT evaluation biases
Markus Freitag, Isaac Caswell, and Scott Roy. 2019 · 2019
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Results of the WMT19 Metrics Shared Task: Segment-Level and Strong MT Systems Pose Big Challenges
Qingsong Ma, Johnny Wei, Ondřej Bojar, and Yvette Graham. 2019 · 2019
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Exploiting source-side monolingual data in neural machine translation
Jiajun Zhang and Chengqing Zong. 2016 · 2016
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On integrating a language model into neural machine translation
Caglar Gulcehre, Orhan Firat, Kelvin Xu, Kyunghyun Cho, and Yoshua Bengio. 2017 · 2017
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Unsupervised pretraining for sequence to sequence learning
Prajit Ramachandran, Peter Liu, and Quoc Le. 2017 · 2017
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The effect of translationese on tuning for statistical machine translation
Sara Stymne. 2017 · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Ł ukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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Findings of the 2018 conference on machine translation (WMT18)
Ondřej Bojar, Christian Federmann, Mark Fishel, Yvette Graham, Barry Haddow, Philipp Koehn, and Christof Monz. 2018 · 2018
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Using monolingual data in neural machine translation: a systematic study
Franck Burlot and François Yvon. 2018 · 2018
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Jiajun Shen, Peng-Jen Chen, Matt Le, Junxian He, Jiatao Gu, Myle Ott, Michael Auli, and Marc’Aurelio Ranzato. 2019 · 2019
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Exploiting monolingual data at scale for neural machine translation
Lijun Wu, Yiren Wang, Yingce Xia, Tao Qin, Jianhuang Lai, and Tie-Yan Liu. 2019 · 2019
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The effect of translationese in machine translation test sets
Mike Zhang and Antonio Toral. 2019 · 2019
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How human is machine translationese? comparing human and machine translations of text and speech
Yuri Bizzoni, Tom S Juzek, Cristina España-Bonet, Koel Dutta Chowdhury, Josef van Genabith, and Elke Teich. 2020 · 2020
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On the evaluation of machine translation systems trained with back-translation
Sergey Edunov, Myle Ott, Marc’Aurelio Ranzato, and Michael Auli. 2020 · 2020
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Bleu might be guilty but references are not innocent
Markus Freitag, David Grangier, and Isaac Caswell. 2020 · 2020
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Tagged back-translation revisited: Why does it really work?
Benjamin Marie, Raphael Rubino, and Atsushi Fujita. 2020 · 2020
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Tangled up in BLEU: Reevaluating the evaluation of automatic machine translation evaluation metrics
Nitika Mathur, Timothy Baldwin, and Trevor Cohn. 2020 · 2020
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Translationese as a language in “multilingual” NMT
Parker Riley, Isaac Caswell, Markus Freitag, and David Grangier. 2020 · 2020
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