An innovative approach to autocorrecting grammatical errors in Arabic texts

Moukrim, Chouaib; Tragha, Abderrahim; Benlahmar, El Habib; Tarik, Almalki

doi:10.1016/j.jksuci.2019.02.005

Cited by 12 publications

(7 citation statements)

References 8 publications

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“…It would be interesting to compare this work with others. However, there are no available systems on the correction of the grammatical case ending errors in Arabic except for the research study [13] of the same team that developed the present work. Furthermore, it is not practicable to make a comparison for other languages.…”

Section: A Summary Of the Evaluation Results Is Presented Inmentioning

confidence: 99%

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The Correction of the Grammatical Case Endings Errors in Arabic Language

Moukrim¹,

Tragha²,

Benlahmer³

2019

IJACSA

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Syntax plays a key role in natural language processing, but it does not always occupy an important position in applications. The main objective of this article is to solve the problem of the grammatical case ending errors produced by Arabic learners or certain common errors. Arabic can be considered more complex than English or French. He does not have vowels; diacritic signs (vowels) are placed above or below the letters. These diacritic signs are abandoned in most Arabic texts. This induces both grammatical and lexical ambiguities in Arabic. The present paper describes an automatic correction of this type of errors using "Stanford Parser" with an ontology containing the rules of the Arabic language. We segment the text into sentences, then we extract the annotations of each word with the syntactic relations coming from our parser, then we treat the relations obtained with our ontology. Finally, we compare the original sentence with the corrected one in order to detect the error. The implemented system achieved a total detection of about 94%. It is concluded that the approach is clearly promising by observing the results as compared to the limited number of available Arabic grammar checkers.

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Section: A Summary Of the Evaluation Results Is Presented Inmentioning

confidence: 99%

“…We have also contributed to this field by a new approach based on the automatic generation of correct sentences [13]. This is a very interesting study because we are devoting an important area of Arabic grammar, namely the grammatical case endings.…”

Section: Related Workmentioning

confidence: 99%

The Correction of the Grammatical Case Endings Errors in Arabic Language

Moukrim¹,

Tragha²,

Benlahmer³

2019

IJACSA

Self Cite

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“…e second study on Arabic grammar checkers was presented by Moukrim et al [35]. Apparently, their system uses the Arabic grammar described in the ontology [36] to generate constraints and sentence rules.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Some improvements have been made to this work, as demonstrated in [37], using a Stanford parser to segment and annotate the input sentences. en, they adopted the same two assumptions they mentioned in [35] ), the syntactic dependency in the adjective, the adverb, and the permutation with its noun. e grammar check was 94.28% accurate on the four types of errors, using only 100 sentences.…”

Section: Literature Reviewmentioning

confidence: 99%

An Arabic Grammar Auditor Based on Dependency Grammar

Alothman

Al-Salman

2020

Advances in Human-Computer Interaction

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The Arabic language has many complex grammar rules that may seem complicated to the average user or learner. Automatic grammar checking systems can improve the quality of the text, reduce the costs of the proofreading process, and play a role in grammar teaching. This paper presents an initiative toward developing a novel and comprehensive Arabic auditor that can address vowelized texts. We called the “Arabic Grammar Detector” (AGD-أَجِــدْ). AGD was successfully implemented based on a dependency grammar and decision tree classifier model. Its purpose is to extract patterns of grammatical rules from a projective dependency graph in order to designate the appropriate syntax dependencies of a sentence. The current implementation covers almost all regular Arabic grammar rules for nonvowelized texts as well as partially or fully vowelized texts. AGD was evaluated using the Tashkeela corpus. It can detect more than 94% of grammatical errors and hint at their causes and possible corrections.

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“…Grammatical ambiguity occurs due to incorrect grammar usage. However, this ambiguity would disappear once it is used within a sentence [1][2][3][4]. In Indonesian, the unability to understand ambiguous sentences often occurs due to different levels of language use, different levels of education, and culture [5].…”

Section: Introductionmentioning

confidence: 99%

Detecting Indonesian ambiguous sentences using Boyer-Moore algorithm

et al. 2020

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Ambiguous sentences are divided into 3 types namely phonetic, lexical, and grammatical. This study focuses on grammatical ambiguous sentences, grammatical ambiguous sentences are ambiguities that occur due to incorrect grammar, but this ambiguity will disappear once it is used within a sentence. Ambiguous sentences become a big problem when they are processed by a computer. In order for the computer to interpret ambiguous words correctly, this study seeks to develop detection of Indonesian ammbiguous sentences using Boyer Moore algorithm. This algorithm matches ambiguous sentences that are inserted as input with the data set. Then the sentence is being detected whether it contains ambiguous sentences, by calculating the percentage of similarity using cosine similarity method. Cosine similarity system is able to find out the meaning of the sentence. In the data set, the number of ambiguous sentences that can be collected is 50 words. The 50 words consist of ambiguous words data, ambiguous sentences, and ambiguous sentence meanings. This system trial was carried out for 200 times and the accuracy level was 0.935, precision was 0.9320, and Recall was 0.8. While the F-Measure was 0.8061. While the speed for word search 0.003275 seconds

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An innovative approach to autocorrecting grammatical errors in Arabic texts

Cited by 12 publications

References 8 publications

The Correction of the Grammatical Case Endings Errors in Arabic Language

The Correction of the Grammatical Case Endings Errors in Arabic Language

An Arabic Grammar Auditor Based on Dependency Grammar

Detecting Indonesian ambiguous sentences using Boyer-Moore algorithm

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