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This paper introduces the work on building a machine translation system for Arabic-to-Turkish in the news domain. Our work includes collecting parallel datasets in several ways for a new and low-resource language pair, building baseline systems with state-ofthe-art architectures and developing language specific algorithms for better translation. Parallel datasets are mainly collected three different ways; i) translating Arabic texts into Turkish by professional translators, ii) exploiting the web for open-source Arabic-Turkish parallel texts, iii) using back-translation. We performed preliminary experiments for Arabicto-Turkish machine translation with neural (Marian) machine translation tools with a novel morphologically motivated vocabulary reduction method.