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Selecting Backtranslated Data From Multiple Sources For Improved Neural Machine Translation.pdf

Selecting Backtranslated Data from Multiple Sources for Improved Neural Machine Translation.pdf
Preview of Selecting Backtranslated Data from Multiple Sources for Improved Neural Machine Translation.pdf
🔗 Source: ixa.si.ehu.eus
📊 Size: 487 KB
📄 Pages: 11 pages
⬇️ Downloads: 71

Summary

Researchers analyzed the impact of backtranslated data from different sources on neural machine translation (NMT) systems, using a low-resource language pair (Basque-to-Spanish) and a high-resource pair (German-to-English). They combined backtranslated data from rule-based, phrase-based statistical, and neural MT systems, and employed data selection strategies to optimize the synthetic corpora. The results showed that incorporating backtranslated data from different sources can be beneficial, and that using data selection can yield improved performance. The study also investigated the effect of data selection on the quality and lexical diversity of the resulting corpora, and found that taking into account the quality of the MT systems used for backtranslation and the lexical diversity of the resulting corpora can lead to better results.

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Researchers analyzed the impact of backtranslated data from different sources on neural machine translation (NMT) systems, using a low-resource language pair...

Technical Information

  • File Format: PDF
  • File Size: 487 KB
  • Pages: 11
  • Language: EN
  • Total Downloads: 71
  • Last Updated: 3 hours ago

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This PDF document about Selecting Backtranslated Data from Multiple Sources for Improved Neural Machine Translation.pdf provides comprehensive information and guidance. Whether you're a beginner or advanced user, this resource offers valuable insights into Selecting Backtranslated Data from Multiple Sources for Improved Neural Machine Translation.pdf.

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