Moses
statistical
machine translation
system

Welcome to Moses!

Moses is a statistical machine translation system that allows you to automatically train translation models for any language pair. All you need is a collection of translated texts (parallel corpus). An efficient search algorithm finds quickly the highest probability translation among the exponential number of choices.

News

  • Moses development is being supported by the EU under the MosesCore project
  • Moses now has a cruise control page to see the status of the current builds
  • Moses is now hosted on github

Features

Get started

The released software includes a command line executable which can used for decoding. The source code for the decoder, can be downloaded from github. Download the complete snapshot from github. This repository also contains regression tests, should you be interested in enhancing the decoder.

Learn about the decoder, training models, and tuning. Follow the step-by-step guide. The documentation available at this web side is also compiled in a printable manual.

Acknowledgement

The development of Moses is mainly supported under the MosesCore, EuroMatrixPlus, LetsMT, EuroMatrix, META-NET, and TC-STAR projects funded by the European Commission under Framework Programme 7 and 6, and received additional support from

  • University of Edinburgh, Scotland
  • Charles University, Prague, Czech Republic
  • Fondazione Bruno Kessler, Trento, Italy
  • RWTH Aachen, Germany
  • University of Maryland, College Park, United States
  • Massachusetts Institute of Technology, United States
  • US funding agencies DARPA, NSF, and Department of Defence

Open Source License

Moses is licensed under the LGPL.

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Page last modified on March 23, 2012, at 03:37 PM