Mining Parenthetical Translations from the Web by Word Alignment

Documents in languages such as Chinese, Japanese and Korean sometimes annotate terms with their translations in English inside a pair of parentheses. We present a method to extract such translations from a large collec-tion of web documents by building a partially parallel corpus and use a word alignment al-gorithm to identify the terms being translated. The method is able to generalize across the translations for different terms and can relia-bly extract translations that occurred only once in the entire web. Our experiment on Chinese web pages produced more than 26 million pairs of translations, which is over two orders of magnitude more than previous re-sults. We show that the addition of the ex-tracted translation pairs as training data provides significant increase in the BLEU score for a statistical machine translation sys-tem.