Word Segmentation of Informal Arabic with Domain Adaptation

Segmentation of clitics has been shown to improve accuracy on a variety of Arabic NLP tasks. However, state-of-the-art Ara-bic word segmenters are either limited to formal Modern Standard Arabic, perform-ing poorly on Arabic text featuring dialectal vocabulary and grammar, or rely on lin-guistic knowledge that is hand-tuned for each dialect. We extend an existing MSA segmenter with a simple domain adapta-tion technique and new features in order to segment informal and dialectal Arabic text. Experiments show that our system outperforms existing systems on newswire, broadcast news and Egyptian dialect, im-proving segmentation F1 score on a recently released Egyptian Arabic corpus to 95.1%, compared to 90.8 % for another segmenter designed specifically for Egyptian Arabic. 1