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Erschienen in:
2004 | OriginalPaper | Buchkapitel
Towards an Efficient Evolutionary Decoding Algorithm for Statistical Machine Translation
verfasst von : Eridan Otto, María Cristina Riff
Erschienen in: MICAI 2004: Advances in Artificial Intelligence
Verlag: Springer Berlin Heidelberg
Enthalten in: Professional Book Archive
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In a statistical machine translation system (SMTS), decoding is the process of finding the most likely translation based on a statistical model according to previously learned parameters. This paper proposes a new approach based on evolutionary hybrid algorithms to translate sentences in a specific technical context. The tests are carried out in the context of Spanish and then translated to English. The experimental results validate the performance of our method.