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Decoding for Word Based Models

When decoding was first encountered in word-based models, a quite diverse set of decoding algorithms was explored.

Word Based Decoding is the main subject of 5 publications. 4 are discussed here.

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Several decoding methods for word-based models are compared by Germann et al. (2001), who introduce a greedy search (Germann, 2003) and integer programming search method. Search errors of the greedy decoder may be reduces by a better initialization, for instance using an example-based machine translation system for seeding the search (Paul et al., 2004). A decoding algorithm based on alternately optimizing alignment (given translation) and translation (given alignment) is proposed by Udupa et al. (2004).

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  • Riedel and Clarke (2009)

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