Word Segmentation of Informal Arabic with Domain Adaptation

@inproceedings{Monroe2014WordSO,
  title={Word Segmentation of Informal Arabic with Domain Adaptation},
  author={Will Monroe and Spence Green and Christopher D. Manning},
  booktitle={ACL},
  year={2014}
}
Segmentation of clitics has been shown to improve accuracy on a variety of Arabic NLP tasks. However, state-of-the-art Arabic word segmenters are either limited to formal Modern Standard Arabic, performing poorly on Arabic text featuring dialectal vocabulary and grammar, or rely on linguistic knowledge that is hand-tuned for each dialect. We extend an existing MSA segmenter with a simple domain adaptation technique and new features in order to segment informal and dialectal Arabic text… CONTINUE READING
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Key Quantitative Results

  • Experiments show that our system outperforms existing systems on broadcast news and Egyptian dialect, improving segmentation F1 score on a recently released Egyptian Arabic corpus to 92.09%, compared to 91.60% for another segmenter designed specifically for Egyptian Arabic.

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