  In this article, we present a rule-based approach for transliterating two
mostly used orthographies in Sorani Kurdish. Our work consists of detecting a
character in a word by removing the possible ambiguities and mapping it into
the target orthography. We describe different challenges in Kurdish text mining
and propose novel ideas concerning the transliteration task for Sorani Kurdish.
Our transliteration system, named Wergor, achieves 82.79% overall precision and
more than 99% in detecting the double-usage characters. We also present a
manually transliterated corpus for Kurdish.
