Extract Domain-specific Paraphrase from Monolingual Corpus for Automatic Evaluation of Machine Translation

Paraphrase can help match synonyms or match phrases with the same or similar meaning, thus it plays an important role in automatic evaluation of machine translation. The traditional approaches extract paraphrase in general domain from bilingual corpus. Because the WMT16 metrics task consists of three subtasks, namely news domain, medical domain, and IT domain, we propose to extract domainspecific paraphrase tables from monolingual corpus to replace the general paraphrase table. We utilize the M-L approach to filter the large scale general monolingual corpus into a domain-specific sub-corpus, and exploit Markov Network model to extract paraphrase tables from the sub-corpus. The experimental results on WMT15 Metrics task show that METEOR metric using the domain-specific paraphrase tables outperforms that using the paraphrase table in general domain extracted from the bilingual corpus.

• Publication year

  2016

• Venue

  Conference on Machine Translation

• Publication date

  Unknown publication date

• Fields of study

  Computer Science

• Identifiers
  DOI 10.18653/v1/W16-2343
• 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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