Greg Hanneman


2020

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How Should Markup Tags Be Translated?
Greg Hanneman | Georgiana Dinu
Proceedings of the Fifth Conference on Machine Translation

The ability of machine translation (MT) models to correctly place markup is crucial to generating high-quality translations of formatted input. This paper compares two commonly used methods of representing markup tags and tests the ability of MT models to learn tag placement via training data augmentation. We study the interactions of tag representation, data augmentation size, tag complexity, and language pair to show the drawbacks and benefits of each method. We construct and release new test sets containing tagged data for three language pairs of varying difficulty.

2018

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Leveraging Data Resources for Cross-Linguistic Information Retrieval Using Statistical Machine Translation
Steve Sloto | Ann Clifton | Greg Hanneman | Patrick Porter | Donna Gates | Almut Hildebrand | Anish Kumar
Proceedings of the 13th Conference of the Association for Machine Translation in the Americas (Volume 2: User Track)

2014

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The CMU Machine Translation Systems at WMT 2014
Austin Matthews | Waleed Ammar | Archna Bhatia | Weston Feely | Greg Hanneman | Eva Schlinger | Swabha Swayamdipta | Yulia Tsvetkov | Alon Lavie | Chris Dyer
Proceedings of the Ninth Workshop on Statistical Machine Translation

2013

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The CMU Machine Translation Systems at WMT 2013: Syntax, Synthetic Translation Options, and Pseudo-References
Waleed Ammar | Victor Chahuneau | Michael Denkowski | Greg Hanneman | Wang Ling | Austin Matthews | Kenton Murray | Nicola Segall | Alon Lavie | Chris Dyer
Proceedings of the Eighth Workshop on Statistical Machine Translation

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Improving Syntax-Augmented Machine Translation by Coarsening the Label Set
Greg Hanneman | Alon Lavie
Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

2012

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The CMU-Avenue French-English Translation System
Michael Denkowski | Greg Hanneman | Alon Lavie
Proceedings of the Seventh Workshop on Statistical Machine Translation

2011

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Automatic Category Label Coarsening for Syntax-Based Machine Translation
Greg Hanneman | Alon Lavie
Proceedings of Fifth Workshop on Syntax, Semantics and Structure in Statistical Translation

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A General-Purpose Rule Extractor for SCFG-Based Machine Translation
Greg Hanneman | Michelle Burroughs | Alon Lavie
Proceedings of Fifth Workshop on Syntax, Semantics and Structure in Statistical Translation

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CMU Syntax-Based Machine Translation at WMT 2011
Greg Hanneman | Alon Lavie
Proceedings of the Sixth Workshop on Statistical Machine Translation

2010

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Improved Features and Grammar Selection for Syntax-Based MT
Greg Hanneman | Jonathan Clark | Alon Lavie
Proceedings of the Joint Fifth Workshop on Statistical Machine Translation and MetricsMATR

2009

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Machine Translation System Combination with Flexible Word Ordering
Kenneth Heafield | Greg Hanneman | Alon Lavie
Proceedings of the Fourth Workshop on Statistical Machine Translation

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An Improved Statistical Transfer System for French-English Machine Translation
Greg Hanneman | Vamshi Ambati | Jonathan H. Clark | Alok Parlikar | Alon Lavie
Proceedings of the Fourth Workshop on Statistical Machine Translation

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Decoding with Syntactic and Non-Syntactic Phrases in a Syntax-Based Machine Translation System
Greg Hanneman | Alon Lavie
Proceedings of the Third Workshop on Syntax and Structure in Statistical Translation (SSST-3) at NAACL HLT 2009

2008

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Statistical Transfer Systems for French-English and German-English Machine Translation
Greg Hanneman | Edmund Huber | Abhaya Agarwal | Vamshi Ambati | Alok Parlikar | Erik Peterson | Alon Lavie
Proceedings of the Third Workshop on Statistical Machine Translation