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Machine Translation.pdf

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Preview of Machine Translation
🔗 Source: ahcweb01.naist.jp
📊 Size: 288 KB
📄 Pages: 4 pages
⬇️ Downloads: 163

Summary

Machine translation has seen significant advancements in the past decade, with five major elements contributing to its progress: rule-based machine translation (RBMT), statistical machine translation (SMT), phrase-based machine translation (PBMT), automatic evaluation, and discriminative training. RBMT uses hand-coded rules to translate text, while SMT uses statistical models to learn translation patterns from data. PBMT is a type of SMT that translates phrases rather than individual words. Automatic evaluation metrics, such as BLEU and RIBES, measure the quality of machine translations. Discriminative training methods, like minimum error rate training (MERT), optimize translation models to minimize errors. These advancements have enabled machine translation to be used in real-world applications, with systems like Google Translate and Moses achieving high-quality translations.

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Description

Machine translation has seen significant advancements in the past decade, with five major elements contributing to its progress: rule-based machine translation...

Technical Information

  • File Format: PDF
  • File Size: 288 KB
  • Pages: 4
  • Language: EN
  • Total Downloads: 163
  • Last Updated: 4 hours ago

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This PDF document about Machine Translation provides comprehensive information and guidance. Whether you're a beginner or advanced user, this resource offers valuable insights into Machine Translation.

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