Generation of Word Graphs in Statistical Machine Translation

Statistical machine translation systems usually compute the single sentence that has the highest probability according to the models that are trained on data. We describe a method for constructing a word graph to represent alternative hypotheses in an efficient way. The advantage is that these hypotheses can be rescored using a refined language or translation model. Results are presented on the German-English Verbmobil corpus.

• Publication year

  2002

• Venue

  Conference on Empirical Methods in Natural Language Processing

• Publication date

  2002-07-06

• Fields of study

  Linguistics, Computer Science

• Identifiers
  DOI 10.3115/1118693.1118714
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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