Abstract
We present experiments with a Moses-based English-to-Hindi translation system. We evaluate the impact of additional out-of-domain training data, both parallel and Hindi-only, and experiment with three methods for improving word order: standard Moses reordering model, rule-based preprocessing and language-independent suffix identification.