CNRC-TMT: Second Language Writing Assistant System Description

We describe the system entered by the National Research Council Canada in the SemEval-2014 L2 writing assistant task. Our system relies on a standard Phrase-Based Statistical Machine Translation trained on generic, publicly available data. Translations are produced by taking the already translated part of the sentence as fixed context. We show that translation systems can address the L2 writing assistant task, reaching out-of-five word-based accuracy above 80 percent for 3 out of 4 language pairs. We also present a brief analysis of remaining errors.

• Publication year

  2014

• Venue

  International Workshop on Semantic Evaluation

• Publication date

  2014-08-01

• Fields of study

  Linguistics, Computer Science

• Identifiers
  DOI 10.3115/v1/S14-2030
• 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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