This is a new version of the repository. Do let us know (lindat-help at ufal.mff.cuni.cz) if you encounter any issues.

Manual Arabic spelling-errors correction for collected documents

Please use the following text to cite this item or export to a predefined format:
Saty, Ahmed; Aouragh, Si Lhoussain and Bouzoubaa, Karim, 2023, Manual Arabic spelling-errors correction for collected documents, LINDAT/CLARIAH-CZ digital library at the Institute of Formal and Applied Linguistics (ÚFAL), http://hdl.handle.net/11372/LRT-4763.
Date issued
2023-03-06
Size
619 kb
Language(s)
Description
The file represents a text corpus in the context of Arabic spell checking, where a group of persons edited different files, and all of the committed spelling errors by these persons have been recorded. A comprehensive representation these persons’ profile has been considered: male, female, old-aged, middle-aged, young-aged, high and low computer usage users, etc. Through this work, we aim to help researchers and those interested in Arabic NLP by providing them with an Arabic spell check corpus ready and open to exploitation and interpretation. This study also enabled the inventory of most spelling mistakes made by editors of Arabic texts. This file contains the following sections (tags): people – documents they printed – types of possible errors – errors they made. Each section (tag) contains some data that explains its details and its content, which helps researchers extracting research-oriented results. The people section contains basic information about each person and its relationship of using the computer, while the documents section clarifies all sentences in each document with the numbering of each sentence to be used in the errors section that was committed. We are also adding the “type of errors” section in which we list all the possible errors with their description in the Arabic language and give an illustrative example.
 Files in this item
Name
manual Spelling-errors correction.xml
Size
618.86 KB
Format
text/xml
Description
Unknown
MD5
a2d7a7e10c4f7836079ca15da4952e65
Preview
  File Preview