This paper describes our approach to English-Korean transliteration in NEWS 2011 Shared Task on Machine Transliteration. We adopt the substring-based transliteration approach which group the characters of named entity in both source and target languages into substrings and then formulate the transliteration as a sequential tagging problem to tag the substrings in the source language with the substrings in the target language. The CRF algorithm are used to deal with this tagging problem. We also construct a rulebased transliteration method for comparison. Our standard and non-standard runs achieves 0.43 and 0.332 in top-1 accuracy which were ranked as the best for the English-Korean pair.
In other language, REF worked on the English-Korean translation.
English-Korean Named Entity Transliteration Using Statistical Substring-based and Rule-based Approaches
NEWS@IJCNLP
Computer Science