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%.
Highlights
Dyslexia is defined as a neurobiological condition characterised by an individual’s inability to read, spell, decode text and recognise words accurately or fluently [1]
The types of errors handled in the data of previous studies were punctuation errors, grammar errors, real spelling errors and non-word spelling errors; this study examines the spelling errors made by dyslexic writers of Arabic text
The Sahah system developed for this study was evaluated in two ways: (i) using a Bangor Dyslexic Arabic Corpus (BDAC) corpus that consisted of text written by people with dyslexia; and (ii) using a comparison with commonly-used spellcheckers/tools
Summary
Dyslexia is defined as a neurobiological condition characterised by an individual’s inability to read, spell, decode text and recognise words accurately or fluently [1]. The motivation behind this study, is to develop an Arabic automatic spelling correction system to help dyslexic writers. The purpose of the automatic correction function is to correct spelling errors automatically in the text without the need to manually choose the word from a suggestion list. This is called “autocorrect”, “replace as you type” and “text replacement” [16]. The authors of this paper believe that an effective spelling correction tool for dyslexic writers would be one that corrects the text automatically without requiring that the writer choose the right word out of the suggested list. Section 3.4.2 presents the experimental results, while Section 4 concludes the study
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
