Stanford University’s Arabic-to-English Statistical Machine Translation System for the 2009 NIST Evaluation
- Michel Galley ,
- Spence Green ,
- Daniel Cer ,
- Pi-Chuan Chang ,
- Christopher D. Manning
The 2009 NIST Open Machine Translation Evaluation Meeting |
This document describes Stanford University’s first entry into a NIST Arabic-English MT evaluation. We describe two main improvements over a previous Chinese-English submission (Galley et al., 2008): a hierarchical lexicalized reordering model (Galley and Manning, 2008) and a technique for performing minimum error rate training (Cer et al., 2008) that outperforms the standard Powell method.