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AsoSoft Text Corpus is the first large scale text corpus for the Kurdish language.

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AsoSoft Kurdish Text Corpus Ver 1.0

AsoSoft Text Corpus is the first large-scale Kurdish text corpus for Central Kurdish (Sorani) branch. This text corpus is compiled and processed by AsoSoft R&D Group (http://asosoft.com/en/).

This repository includes the following files:

  1. AsoSoft Text Corpus Large Version: This file contains 75 million tokens.
  2. AsoSoft Text Corpus Small Version:: This file contains 5 million tokens.
  3. AsoSoft topic annotated dataset.

Normalization

A lot of normalization is done on this text corpus, including:

  • Non-unicode characters are converted.
  • Multi-code Unicode Characters are unified and converted to Kurdish characters.
  • Everywhere ("ه"+ "ZWNJ") is used, it is replaced Kurdish "ە".
  • If conjuctive "و" is joined to its previous word, it is separated using a novel suggested algorithm.
  • Everywhere "ر" or "وو" is used as the first letter of words, it is replaced with "ڕ" or "و" correspondingly.
  • ...

More detail about normalization which is done is presented in our paper.

Applications

Asosoft text corpus is applicable for following research areas:

  • Linguistics
  • Lexicography
  • NLP and Speech Processing
    • Extracting language models
    • Word vector representation
    • Topic Identification
    • Extracting computational lexicons

How to Use

Some common editors for work with large text files are: EmEdior, TlCorpus, TextPad and so forth.

License

This text corpus in for non-commercial use and researchers all over the world can use it for research projects.

Cite

If you are using our text corpus cite us.

Hadi Veisi, Mohammad MohammadAmini, Hawre Hosseini; Toward Kurdish language processing: Experiments in collecting and processing the AsoSoft text corpus, Digital Scholarship in the Humanities, , fqy074, https://doi.org/10.1093/llc/fqy074

@article{veisi2020toward,
  title={Toward Kurdish language processing: Experiments in collecting and processing the AsoSoft text corpus},
  author={Veisi, Hadi and MohammadAmini, Mohammad and Hosseini, Hawre},
  journal={Digital Scholarship in the Humanities},
  volume={35},
  number={1},
  pages={176--193},
  year={2020},
  publisher={Oxford University Press}
}