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Statistical Machine Translation by Philipp Koehn

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Chapter 6

Decoding

In the two previous chapters we presented two models for machine translation, one based on the translation of words, and another based on the translation of phrases as atomic units. Both models were defined as mathematical formulae that, given a possible translation, assign a probabilistic score to it.

The task of decoding in machine translation is to find the best scoring translation according to these formulae. This is a hard problem, since there is an exponential number of choices, given a specific input sentence. In fact, it has been shown that the decoding problem for the presented machine translation models is NP-complete [Knight, 1999a]. In other words, exhaustively examining all possible translations, scoring them, ...

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