Paper: A Corpus Level MIRA Tuning Strategy for Machine Translation

ACL ID D13-1083
Title A Corpus Level MIRA Tuning Strategy for Machine Translation
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2013
Authors

MIRA based tuning methods have been widely used in statistical machine translation (SMT) system with a large number of fea- tures. Since the corpus-level BLEU is not de- composable, these MIRA approaches usually define a variety of heuristic-driven sentence- level BLEUs in their model losses. Instead, we present a new MIRA method, which em- ploys an exact corpus-level BLEU to com- pute the model loss. Our method is simpler in implementation. Experiments on Chinese-to- English translation show its effectiveness over two state-of-the-art MIRA implementations.