Moses (machine translation)

MosesDeveloper(s)| University of Edinburgh

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Stable release|

4.0[1] / October 5, 2017; 8 years ago (2017-10-05)

Written in| C++, Perl
Operating system| Windows, Linux, macOS
Type| Machine translation
License| LGPL
Website| statmt.org/moses

Moses is a statistical machine translation engine that can be used to train statistical models of text translation from a source language to a target language, developed by the University of Edinburgh.[2] Moses then allows new source-language text to be decoded using these models to produce automatic translations in the target language. Training requires a parallel corpus of passages in the two languages, typically manually translated sentence pairs. Moses is free and open-source software, released under the GNU Library Public License (LGPL), and available as source code and binary files for Windows[3] and Linux. Its development is supported mainly by the EuroMatrix project, with funding by the European Commission.

Among its features are:

* A beam search algorithm that quickly finds the highest probability translation within a set of choices
* Phrase-based translation of short text chunks
* Handles words with multiple factored representations to enable integrating linguistic and other information (e.g., surface form, lemma and morphology, part-of-speech, word class)
* Decodes ambiguous forms of a source sentence, represented as a confusion network, to support integrating with upstream tools such as speech recognizers
* Support for large language models (LMs) such as IRSTLM (an exact LM using memory-mapping) and RandLM (an inexact LM based on Bloom filters)

## Contents

* 1 See also
* 2 References
* 3 Further reading
* 4 External links

## See also

* Apertium
* OpenLogos
* Comparison of machine translation applications
* Machine translation

## References

1. ↑ "Moses - Releases". http://www.statmt.org/moses/?n=Moses.Releases.
2. ↑ "Moses: Bringing machine translation to the masses". https://www.ed.ac.uk/research/impact/science-engineering/moses.
3. ↑ "Moses" (in en). 2013-11-28. https://www.slideshare.net/slideshow/moses-28697208/28697208.

## Further reading

* Philipp Koehn, Hieu Hoang, Alexandra Birch, Chris Callison-Burch, Marcello Federico, Nicola Bertoldi, Brooke Cowan, Wade Shen, Christine Moran, Richard Zens, Chris Dyer, Ondrej Bojar, Alexandra Constantin, Evan Herbst. (2007) "Moses: Open Source Toolkit for Statistical Machine Translation". Annual Meeting of the Association for Computational Linguistics (ACL), demonstration session, Prague, Czech Republic, June 2007.

## External links

* Official website
* IRST LM Toolkit on SourceForge.net
* RandLM on SourceForge.net

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