How Should Markup Tags Be Translated?

1 code implementation • WMT (EMNLP) 2020 • Greg Hanneman, Georgiana Dinu

The ability of machine translation (MT) models to correctly place markup is crucial to generating high-quality translations of formatted input.

Data Augmentation Machine Translation +2

Leveraging Data Resources for Cross-Linguistic Information Retrieval Using Statistical Machine Translation

no code implementations • WS 2018 • Steve Sloto, Ann Clifton, Greg Hanneman, Patrick Porter, Donna Gates, Almut Hildebrand, Anish Kumar

Information Retrieval Machine Translation +2

The CMU Machine Translation Systems at WMT 2014

no code implementations • WS 2014 • Austin Matthews, Waleed Ammar, Archna Bhatia, Weston Feely, Greg Hanneman, Eva Schlinger, Swabha Swayamdipta, Yulia Tsvetkov, Alon Lavie, Chris Dyer

Lemmatization Machine Translation +1

The CMU Machine Translation Systems at WMT 2013: Syntax, Synthetic Translation Options, and Pseudo-References

no code implementations • WS 2013 • Waleed Ammar, Victor Chahuneau, Michael Denkowski, Greg Hanneman, Wang Ling, Austin Matthews, Kenton Murray, Nicola Segall, Alon Lavie, Chris Dyer

Language Modelling Translation +1

Improving Syntax-Augmented Machine Translation by Coarsening the Label Set

no code implementations • NAACL 2013 • Greg Hanneman, Alon Lavie

Machine Translation Translation

The CMU-Avenue French-English Translation System

no code implementations • WS 2012 • Michael Denkowski, Greg Hanneman, Alon Lavie

Machine Translation Translation