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Automated programming approaches to enhance computer-aided translation accuracy.

Tao Zhao1,2, Mazni Binti Alias1

  • 1Faculty of Management, Multimedia University, Cyberjaya, Malaysia.

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|December 9, 2024
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Summary
This summary is machine-generated.

Computer-assisted translation (CAT) systems using automated programming show improved accuracy in English vocabulary translation compared to traditional manual methods. This advancement enhances translation quality for complex sentences, jargon, and nuances.

Keywords:
Automatic programmingComputer aided translationDeep learningsGraph neural networkTranslation accuracy

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Area of Science:

  • Computational Linguistics
  • Natural Language Processing

Background:

  • Modern translation demands speed and accuracy, challenging traditional manual methods.
  • Computer-assisted translation (CAT) offers speed but requires quality evaluation.
  • English vocabulary presents complexities due to context-dependent meanings.

Purpose of the Study:

  • To compare the accuracy of automated programming-based CAT systems with manual translation for English vocabulary.
  • To identify improvements for CAT systems in handling complex English linguistic elements.

Main Methods:

  • Comparative analysis of translation accuracy between automated CAT and manual translation.
  • Utilizing automated programming and translation memory for CAT system enhancement.
  • Focusing on complex English vocabulary, including jargon, acronyms, and semantic nuances.

Main Results:

  • Automated programming-based CAT systems demonstrated an 8% increase in accuracy over manual translation.
  • CAT systems proved more effective in translating complex English sentences, professional jargon, acronyms, and semantic subtleties.
  • The study validated the premise that automated programming enhances CAT accuracy.

Conclusions:

  • Computer-assisted translation (CAT) systems utilizing automated programming offer superior accuracy for English vocabulary compared to traditional manual translation.
  • CAT technology is a valuable asset for the translation industry, improving efficiency and precision.
  • Further development of CAT systems can enhance their capability to manage linguistic complexities.