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• W2099864888 abstract "This paper presents a novel method to suggest long word reorderings to a phrase-based SMT decoder. We address language pairs where long reordering concentrates on few patterns, and use fuzzy chunk-based rules to predict likely reorderings for these phenomena. Then we use reordered n-gram LMs to rank the resulting permutations and select the n-best for translation. Finally we encode these reorderings by modifying selected entries of the distortion cost matrix, on a per-sentence basis. In this way, we expand the search space by a much finer degree than if we simply raised the distortion limit. The proposed techniques are tested on Arabic-English and German-English using well-known SMT benchmarks." @default.
• W2099864888 created "2016-06-24" @default.
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• W2099864888 date "2012-07-08" @default.
• W2099864888 modified "2023-09-26" @default.
• W2099864888 title "Modified Distortion Matrices for Phrase-Based Statistical Machine Translation" @default.
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