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home / docs / papers / Semitic languages / Camelira: An Arabic Multi-Dialect Morphological Disambiguator

Camelira: An Arabic Multi-Dialect Morphological Disambiguator

What it is about

Camelira is a public web interface that disambiguates Arabic sentences in four varieties: MSA, Egyptian, Gulf and Levantine. Its disambiguator is an existing tagger (Inoue et al., 2022) on top of a morphological analyzer. A dialect identifier, a reimplementation of Salameh et al. (2018), picks the variety-specific disambiguator when the user does not name one. Unlike MADAMIRA or Farasa, the interface shows every analysis of a word with its score, not only the top one. On the DEV split, full-tag accuracy is 95.9% for MSA, 90.5% for Egyptian, 93.8% for Gulf and 85.5% for Levantine (POS-only: 98.7, 94.0, 96.6, 92.7). The dialect identifier reaches 93.5% on TEST, against 93.6% for the original. It is a demonstration paper and reports no new model.

Ideas

For Mova

I1 is for world and the explanation of parses. I2 is for tools/langseg and the variety choice in languages/arc/. I3 is a measurement table for tools/hbo and Aramaic in Mova: what it would need.

Cite

The paper itself, not this card. BibTeX from the library's record of the work. DOI 10.18653/v1/2022.emnlp-demos.32

@inproceedings{obeid2022camelira,
  title = {{Camelira: An Arabic Multi-Dialect Morphological Disambiguator}},
  author = {Obeid, Ossama and Inoue, Go and Habash, Nizar},
  booktitle = {Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations},
  year = {2022},
  doi = {10.18653/v1/2022.emnlp-demos.32},
  url = {https://doi.org/10.18653/v1/2022.emnlp-demos.32}
}

References

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