Improving the Quality of Machine Translations by Providing Stylistic Guidelines to Authors and Editors

Abstract

This research sought to identify stylistic guidelines which could be used by the authors and editors of English language texts in order to improve the quality of subsequent machine translations to other languages. A literature review was conducted to provide background information and to determine what guidelines would be appropriate. Nine guidelines were developed on the basis of the review. The guidelines were then tested. They were applied to five paragraphs from a Royal Australian Air Force technical publication by the researcher and an independent volunteer. Both the resulting texts and the original paragraphs were translated into French using the Globalink Translation System and the quality of the translations obtained was evaluated by four human translators. While the translations of the paragraphs which had been edited by the volunteer were significantly better than the translations of the original texts, the translations of the paragraphs edited by the researcher were not. Use of the guidelines by authors and editors cannot be recommended on the basis of this result. However, analysis of the conduct and results of the research suggested potentially fruitful alternative approaches to the development and testing of guidelines. These approaches are presented as specific recommendations for further research.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1992
Accession Number
ADA258786

Entities

People

  • Edward J. Walsh

Organizations

  • Air Force Institute of Technology

Tags

DTIC Thesaurus Topics

  • Air Force
  • Artificial Intelligence
  • Computational Linguistics
  • Computational Science
  • Computer Programming
  • Computers
  • English Language
  • European Communities
  • Grammars
  • Language
  • Linguistics
  • Literature Surveys
  • Machine Translation
  • Natural Language Processing
  • Natural Languages
  • Translations
  • Word Processors

Readers

  • Computational Linguistics
  • Organizational Process Management (OPM).
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy
  • AI & ML - Information Retrieval
  • AI & ML - Machine Translation