Syllable-based Machine Transliteration with Extra Phrase Features

This paper describes our syllable-based phrase transliteration system for the NEWS 2012 shared task on English-Chinese track and its back. Grapheme-based Transliteration maps the character(s) in the source side to the target character(s) directly. However, character-based segmentation on English side will cause ambiguity in alignment step. In this paper we utilize Phrase-based model to solve machine transliteration with the mapping between Chinese characters and English syllables rather than English characters. Two heuristic rulebased syllable segmentation algorithms are applied. This transliteration model also incorporates three phonetic features to enhance discriminative ability for phrase. The primary system achieved 0.330 on Chinese-English and 0.177 on English-Chinese in terms of top-1 accuracy.