Towards Machine Translation for the Kurdish Language

TL;DR

This paper explores the challenges and potential solutions for developing a neural machine translation system for the under-resourced Kurdish Sorani dialect, emphasizing data scarcity and text processing techniques.

Contribution

It provides an analysis of available data, discusses key challenges, and demonstrates how fundamental text processing can enhance Kurdish machine translation.

Findings

Scarce parallel data for Sorani Kurdish-English translation

Tokenization improves translation performance

Identifies major challenges in Kurdish language translation

Abstract

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.