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Computers 2019, 8(1), 19; https://doi.org/10.3390/computers8010019

Automatic Correction of Arabic Dyslexic Text

1
School of Computer Science and Information Technology, Albaha University, Albaha 65431, Saudi Arabia
2
School of Computer Science, Bangor University, Bangor LL57 1UT, UK
*
Author to whom correspondence should be addressed.
Received: 31 December 2018 / Revised: 31 January 2019 / Accepted: 1 February 2019 / Published: 21 February 2019
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Abstract

This paper proposes an automatic correction system that detects and corrects dyslexic errors in Arabic text. The system uses a language model based on the Prediction by Partial Matching (PPM) text compression scheme that generates possible alternatives for each misspelled word. Furthermore, the generated candidate list is based on edit operations (insertion, deletion, substitution and transposition), and the correct alternative for each misspelled word is chosen on the basis of the compression codelength of the trigram. The system is compared with widely-used Arabic word processing software and the Farasa tool. The system provided good results compared with the other tools, with a recall of 43%, precision 89%, F1 58% and accuracy 81%. View Full-Text
Keywords: Arabic; corpus; dyslexia; errors; spelling Arabic; corpus; dyslexia; errors; spelling
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Alamri, M.M.; Teahan, W.J. Automatic Correction of Arabic Dyslexic Text. Computers 2019, 8, 19.

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