Syllable-based Machine Transliteration with Extra Phrase Features

摘要

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 rule-based 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.