5 citations · 11 across the 3 of their papers we have counts for
3 papers
Using Interlinear Glosses as Pivot in Low-Resource Multilingual Machine Translation
Zhong Zhou, Lori Levin, David R. Mortensen +1
We demonstrate a new approach to Neural Machine Translation (NMT) for low-resource languages using a ubiquitous linguistic resource, Interlinear Glossed Text (IGT). IGT represents…
The ARIEL-CMU Systems for LoReHLT18
Aditi Chaudhary, Siddharth Dalmia, Junjie Hu +27
This paper describes the ARIEL-CMU submissions to the Low Resource Human Language Technologies (LoReHLT) 2018 evaluations for the tasks Machine Translation (MT), Entity Discovery a…
Semantically-Informed Syntactic Machine Translation: A Tree-Grafting Approach
Kathryn Baker, Michael Bloodgood, Chris Callison-Burch +5
We describe a unified and coherent syntactic framework for supporting a semantically-informed syntactic approach to statistical machine translation. Semantically enriched syntactic…