Paper: Online Large-Margin Training for Statistical Machine Translation

ACL ID D07-1080
Title Online Large-Margin Training for Statistical Machine Translation
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2007
Authors

We achieved a state of the art performance in statistical machine translation by using a large number of features with an online large-margin training algorithm. The mil- lions of parameters were tuned only on a small development set consisting of less than 1K sentences. Experiments on Arabic-to- English translation indicated that a model trained with sparse binary features outper- formed a conventional SMT system with a small number of features.