- Abstract:
- We describe an open-source toolkit for statistical machine translation whose novel contributions are (a) support for linguistically motived 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.
- Links To Paper
- 1st link
- Bibtex format
- @InProceedings{EDI-INF-RR-1222,
- author = {
Philipp Koehn
and Hieu Hoang
and Alexandra Birch-Mayne
and Christopher 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
},
- title = {Moses: Open Source Toolkit for Statistical Machine Translation},
- book title = {Annual Meeting of the Association for Computation Linguistics (ACL), Demonstration Session},
- year = 2007,
- month = {Jun},
- pages = {177-180},
- url = {http://www.iccs.inf.ed.ac.uk/~pkoehn/publications/acl2007-moses.pdf},
- }
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