  Machine translation is the task of translating texts from one language to
another using computers. It has been one of the major tasks in natural language
processing and computational linguistics and has been motivating to facilitate
human communication. Kurdish, an Indo-European language, has received little
attention in this realm due to the language being less-resourced. Therefore, in
this paper, we are addressing the main issues in creating a machine translation
system for the Kurdish language, with a focus on the Sorani dialect. We
describe the available scarce parallel data suitable for training a neural
machine translation model for Sorani Kurdish-English translation. We also
discuss some of the major challenges in Kurdish language translation and
demonstrate how fundamental text processing tasks, such as tokenization, can
improve translation performance.
