Publications

Incident-driven machine translation and name tagging for low-resource languages

Abstract

We describe novel approaches to tackling the problem of natural language processing for low-resource languages. The approaches are embodied in systems for name tagging and machine translation (MT) that we constructed to participate in the NIST LoReHLT evaluation in 2016. Our methods include universal tools, rapid resource and knowledge acquisition, rapid language projection, and joint methods for MT and name tagging.

Date
January 1, 1970
Authors
Ulf Hermjakob, Qiang Li, Daniel Marcu, Jonathan May, Sebastian J Mielke, Nima Pourdamghani, Michael Pust, Xing Shi, Kevin Knight, Tomer Levinboim, Kenton Murray, David Chiang, Boliang Zhang, Xiaoman Pan, Di Lu, Ying Lin, Heng Ji
Journal
Machine Translation
Volume
32
Pages
59-89
Publisher
Springer Netherlands