Machine transliteration of names in Arabic text

  • Authors:
  • Yaser Al-Onaizan;Kevin Knight

  • Affiliations:
  • University of Southern California, Marina del Rey, CA;University of Southern California, Marina del Rey, CA

  • Venue:
  • SEMITIC '02 Proceedings of the ACL-02 workshop on Computational approaches to semitic languages
  • Year:
  • 2002

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Abstract

We present a transliteration algorithm based on sound and spelling mappings using finite state machines. The transliteration models can be trained on relatively small lists of names. We introduce a new spelling-based model that is much more accurate than state-of-the-art phonetic-based models and can be trained on easier-to-obtain training data. We apply our transliteration algorithm to the transliteration of names from Arabic into English. We report on the accuracy of our algorithm based on exact-matching criterion and based on human-subjective evaluation. We also compare the accuracy of our system to the accuracy of human translators.