The impact of Arabic morphological segmentation on broad-coverage English-to-Arabic statistical machine translation

@article{AlHaj2011TheIO,
  title={The impact of Arabic morphological segmentation on broad-coverage English-to-Arabic statistical machine translation},
  author={Hassan Al-Haj and Alon Lavie},
  journal={Machine Translation},
  year={2011},
  volume={26},
  pages={3-24}
}
Morphologically rich languages pose a challenge for statistical machine translation (SMT). This challenge is magnified when translating into a morphologically rich language. In this work we address this challenge in the framework of a broad-coverage English-to-Arabic phrase based statistical machine translation (PBSMT). We explore the largest-to-date set of Arabic segmentation schemes ranging from full word form to fully segmented forms and examine the effects on system performance. Our results… CONTINUE READING