Moses: Open source toolkit for statistical machine translation

Philipp Koehn
Hieu Hoang
Alexandra Birch
Chris Callison-Burch
Marcello Federico
Nicola Bertoldi
Brooke Cowan
Wade Shen
Christine Moran
Chris Dyer
Ondrej Bojar
Alexandra Constantin
Evan Herbst
Proceedings of the 45th Annual Meeting of the ACL - Demo and Poster Sessions, Association for Computational Linguistics, Prague, Czech Republic(2007), pp. 177-180

Abstract

We describe an open-source toolkit for statistical machine translation whose novel contributions are (a) support for linguistically motivated factors,(b) confusion network decoding, and (c) efficient data formats for translation models and language models. In addition to the SMT decoder, the toolkit also includes a wide variety of tools for training, tuning and applying the system to many translation tasks.

Research Areas