Statistical Machine Translation
Statistical machine translation (SMT) deals with automatically mapping sentences in one human language (for example, French) into another human language (such as English). The first language is called the source and the second language is called the target. This process can be thought of as a stochastic process. There are many SMT variants, depending upon how translation is modeled. Some approaches are in terms of a string-to-string mapping, some use trees-to-strings, and some use tree-to-tree models. All share in common the central idea that translation is automatic, with models estimated from parallel corpora (source-target pairs) and also from monolingual corpora (examples of target sentences).
Motivation and Background
Machine Translation has widespread commercial, military, and political applications. For example, increasingly, the Web is accessed by non-English speakers reading non-English pages. The ability to find relevant information clearly should not...
- Brown, P. F., Pietra, S. D., Pietra, V. J. D., & Mercer, R. L. (1994). The mathematic of statistical machine translation: Parameter estimation. Computational Linguistics, 19(2), 263–311.Google Scholar
- Chiang, D. (2005, June). A hierarchical phrase-based model for statistical machine translation. In Proceedings of the 43rd annual meeting of the association for computational linguistics (ACL’05) (pp. 263–270). Ann Arbor, MI: Association for Computational Linguistics.Google Scholar
- Koehn, P., Och, F. J., & Marcu, D. (2003). Statistical phrase-based translation. In NAACL ’03: Proceedings of the 2003 conference of the north american chapter of the association for computational linguistics on human language technology (pp. 48–54). Morristown, NJ: Association for Computational Linguistics.CrossRefGoogle Scholar
- Och, F. J., & Ney, H. (2001). Discriminative training and maximum entropy models for statistical machine translation. In ACL ’02: Proceedings of the 40th annual meeting on association for computational linguistics (pp. 295–302). Morristown, NJ: Association for Computational Linguistics.CrossRefGoogle Scholar
- Papineni, K., Roukos, S., Ward, T., & Zhu, W. -J. (2001). Bleu: A method for automatic evaluation of machine translation. In ACL ’02: Proceedings of the 40th annual meeting on association for computational linguistics (pp. 311–318). Morristown, NJ: Association for Computational Linguistics.CrossRefGoogle Scholar