Crego, JM and Mariño, JB and De Gispert, A (2005) An ngram-based statistical machine translation decoder. 9th European Conference on Speech Communication and Technology. pp. 3185-3188.Full text not available from this repository.
In this paper we describe MARIE, an Ngram-based statistical machine translation decoder. It is implemented using a beam search strategy, with distortion (or reordering) capabilities. The underlying translation model is based on an Ngram approach, extended to introduce reordering at the phrase level. The search graph structure is designed to perform very accurate comparisons, what allows for a high level of pruning, improving the decoder efficiency. We report several techniques for efficiently prune out the search space. The combinatory explosion of the search space derived from the search graph structure is reduced by limiting the number of reorderings a given translation is allowed to perform, and also the maximum distance a word (or a phrase) is allowed to be reordered. We finally report translation accuracy results on three different translation tasks.
|Divisions:||Div F > Machine Intelligence|
|Depositing User:||Unnamed user with email email@example.com|
|Date Deposited:||02 Sep 2016 18:29|
|Last Modified:||08 Dec 2016 06:25|