Statistical Machine Translation of Japanese

Abstract

The purpose of this research was to find ways to improve the performance of a statistical machine translation system that translates text from Japanese to English. Methods included altering the training and test data by adding a prior linguistic knowledge, altering sentence structures, and looking for better ways to statistically alter the way words align between the two languages. In addition, methods for properly segmenting words in Japanese text through statistical methods were examined. Finally, experiments were conducted on Japanese speech to produce the best text transcription of the speech. The best statistical machine translation methods implemented resulted in improvements that rivaled the best evaluations from the 2005 International Workshop on Spoken Language Translation from which training and test data was used. Recommendations, including how the methods presented may be altered for further improvements for future research, are also discussed.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2007
Accession Number
ADA472458

Entities

People

  • Erik A. Chapla

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Air Force
  • Automated Speech Recognition
  • Computational Linguistics
  • Computational Science
  • Electrical Engineering
  • Feature Extraction
  • Grammars
  • Hidden Markov Models
  • Information Science
  • Japanese Language
  • Language
  • Language Translation
  • Linguistics
  • Machine Translation
  • Markov Models
  • Natural Language Processing
  • Probability

Readers

  • Computational Linguistics
  • Computational Modeling and Simulation

Technology Areas

  • AI & ML
  • AI & ML - Machine Translation