Automatic Correction of Arabic Dyslexic Text

Maha Alamri, William Teahan
2019 Computers  
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
more » ... odelength 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%.
doi:10.3390/computers8010019 fatcat:pfjtlsyqyzcpjgimjqsj5d4kdi