Robust Transliteration Mining from Comparable Corpora with Bilingual Topic Models

We present a high-precision, language-independent transliteration framework applicable to bilingual lexicon extrac-tion. Our approach is to employ a bilingual topic model to enhance the output of a state-of-the-art grapheme-based transliteration baseline. We demonstrate that this method is able to extract a high-quality bilingual lexi-con from a comparable corpus, and we extend the topic model to propose a so-lution to the out-of-domain problem.