Next Article in Journal
Software Requirement Specification Based on a Gray Box for Embedded Systems: A Case Study of a Mobile Phone Camera Sensor Controller
Previous Article in Journal
Resource Allocation Model for Sensor Clouds under the Sensing as a Service Paradigm
Open AccessArticle

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.
Computers 2019, 8(1), 19; https://doi.org/10.3390/computers8010019
Received: 31 December 2018 / Revised: 31 January 2019 / Accepted: 1 February 2019 / Published: 21 February 2019
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
Show Figures

Figure 1

MDPI and ACS Style

Alamri, M.M.; Teahan, W.J. Automatic Correction of Arabic Dyslexic Text. Computers 2019, 8, 19.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop