In this work we propose an unsupervised model for deciphering names in two unrelated languages, English and Farsi. The proposed model is a generative non-parametric model that is a customized version of  model for name extraction. We show that this unsupervised model is able to achieve competitive results in comparison with a supervised model. Although the accuracy of the unsupervised model is lower than the supervised model but using this model makes it possible to produce list of parallel names without parallel corpora.
Deciphering, Unrelated languages, Scarce resource languages, English-Farsi, Name extraction