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首页> 外文会议>10th Workshop on statistical machine translation 2015 >Extended Translation Models in Phrase-based Decoding
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Extended Translation Models in Phrase-based Decoding

机译：基于短语的解码中的扩展翻译模型

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摘要

We propose a novel extended translation model (ETM) to counteract some problems in phrase-based translation: The lack of translation context when using single-word phrases and uncaptured dependencies beyond phrase boundaries. The ETM operates on word-level and augments the IBM models by an additional bilingual word pair and a reordering operation. Its implementation in a phrase-based decoder introduces translation and reordering dependencies for single-word phrases and dependencies across phrase boundaries. More, the model incorporates an explicit treatment of multiple and empty alignments. Its integration outperforms competitive systems that include lexical and phrase translation models as well as hierarchical reordering models on 4 language pairs significantly by +0.7% BLEU on average. Although simpler and using fewer dependencies, the ETM proves to be on par with 7-gram operation sequence models (Durrani et al., 2013b).
机译：我们提出了一种新颖的扩展翻译模型（ETM），以解决基于短语的翻译中的一些问题：使用单词短语时缺少翻译上下文以及超出短语边界的未捕获依存关系。 ETM在单词级别上运行，并通过附加的双语单词对和重新排序操作来扩展IBM模型。它在基于短语的解码器中的实现引入了单词短语的翻译和重新排序依赖性以及跨短语边界的依赖性。此外，该模型还包含对多个空对齐的显式处理。它的集成性能优于包括词法和短语翻译模型以及4种语言对的分层重排模型的竞争系统，平均BLEU平均提高了+ 0.7％。尽管更简单并且使用更少的依赖项，但事实证明ETM与7克操作序列模型相当（Durrani等人，2013b）。

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  • 会议地点 Lisbon(PT)
  • 作者

    Andreas Guta; Joern Wuebker; Miguel Graca; Yunsu Kim; Hermann Ney;

  • 作者单位

    Human Language Technology and Pattern Recognition Group RWTH Aachen University Aachen, Germany;

    Human Language Technology and Pattern Recognition Group RWTH Aachen University Aachen, Germany;

    Human Language Technology and Pattern Recognition Group RWTH Aachen University Aachen, Germany;

    Human Language Technology and Pattern Recognition Group RWTH Aachen University Aachen, Germany;

    Human Language Technology and Pattern Recognition Group RWTH Aachen University Aachen, Germany;

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