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This research aims to develop a hierarchical phrase reordering model that enhances long-distance reordering in machine translation systems.

January 1, 2008Open Access

A simple and effective hierarchical phrase reordering model

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This research aims to develop a hierarchical phrase reordering model that enhances long-distance reordering in machine translation systems.
Introduced a novel hierarchical phrase reordering model integrated with standard phrase-based systems.
Evaluated performance using BLEU scores across Chinese-English and Arabic-English language pairs.
Compared the proposed model with existing reordering models in phrase-based systems.
Achieved a BLEU score improvement of +0.53 on MT05 and +0.71 on MT08 for Chinese-English translation.
Obtained a BLEU score improvement of +0.55 on MT05 for Arabic-English translation.

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Randomized trial shows improved phrase reordering in machine translation, indicating enhanced effectiveness for language pairs.

Galley et al. (2008) studied this question.

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