Moses: Open Source Toolkit for Statistical Machine Translation

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.

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@inproceedings{Koehn2007MosesOS, title={Moses: Open Source Toolkit for Statistical Machine Translation}, author={Philipp Koehn and Hieu Hoang and Alexandra Birch and Chris Callison-Burch and Marcello Federico and Nicola Bertoldi and Brooke Cowan and Wade Shen and Christine Moran and Richard Zens and Chris Dyer and Ondrej Bojar and Alexandra Constantin and Evan Herbst}, booktitle={ACL}, year={2007} }