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Journal articles on the topic 'Arabic diacritics'

Author: Grafiati

Published: 5 June 2025

Last updated: 1 August 2025

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1

Azmi, Aqil M., Rehab M. Alnefaie, and Hatim A. Aboalsamh. "Light Diacritic Restoration to Disambiguate Homographs in Modern Arabic Texts." ACM Transactions on Asian and Low-Resource Language Information Processing 21, no. 3 (2022): 1–14. http://dx.doi.org/10.1145/3486675.

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Diacritic restoration (also known as diacritization or vowelization) is the process of inserting the correct diacritical markings into a text. Modern Arabic is typically written without diacritics, e.g., newspapers. This lack of diacritical markings often causes ambiguity, and though natives are adept at resolving, there are times they may fail. Diacritic restoration is a classical problem in computer science. Still, as most of the works tackle the full (heavy) diacritization of text, we, however, are interested in diacritizing the text using a fewer number of diacritics. Studies have shown th

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Sheikh, Ahmed Abdalla, Mohd Sanusi Azmi, Maslita Abd Aziz, Mohammed Nasser Al-Mhiqani, and Salem Saleh Bafjaish. "Framework of diacritic segmentation for Arabic handwritten document." Indonesian Journal of Electrical Engineering and Computer Science 24, no. 2 (2021): 1001–8. https://doi.org/10.11591/ijeecs.v24.i2.pp1001-1008.

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In recent Arabic standard language and Arabic dialectal texts, diacritics and short vowels are absent. There are some exceptions have been made for the Arabic beginner learner scripts, religious texts and as well as a significant political text. In addition, the text without diacritics is considered ambiguous due to numerous words with different diacritic marks seem identical. However, this paper we present a framework for segmenting diacritics from Arabic handwritten document by using region-based segmentation technique. Since Arabic handwritten and Mushaf Al-Quran contain many diacritical ma

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Shiekh, Ahmed Abdalla, Mohd Sanusi Azmi, Maslita Abd Aziz, Mohammed Nasser Al-Mhiqani, and Salem Saleh Bafjaish. "Framework of diacritic segmentation for Arabic handwritten document." Indonesian Journal of Electrical Engineering and Computer Science 24, no. 2 (2021): 1001. http://dx.doi.org/10.11591/ijeecs.v24.i2.pp1001-1008.

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<span lang="EN-US">In <span>recent Arabic standard language and Arabic dialectal texts, diacritics and short vowels are absent. There are some exceptions have been made for the Arabic beginner learner scripts, religious texts and as well as a significant political text. In addition, the text without diacritics is considered ambiguous due to numerous words with different diacritic marks seem identical. However, this paper we present a framework for segmenting diacritics from Arabic handwritten document by using region-based segmentation technique. Since Arabic handwritten and Mushaf

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AZMI, AQIL M., and REHAM S. ALMAJED. "A survey of automatic Arabic diacritization techniques." Natural Language Engineering 21, no. 3 (2013): 477–95. http://dx.doi.org/10.1017/s1351324913000284.

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AbstractIn Modern Standard Arabic texts are typically written without diacritical markings. The diacritics are important to clarify the sense and meaning of words. Lack of these markings may lead to ambiguity even for the natives. Often the natives successfully disambiguate the meaning through the context; however, many Arabic applications, such as machine translation, text-to-speech, and information retrieval, are vulnerable due to lack of diacritics. The process of automatically restoring diacritical marks is called diacritization or diacritic restoration. In this paper we discuss the proper

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Zubeiri, Iman, Adnan Souri, and Badr Eddine El Mohajir. "Arabic text diacritization using transformers: a comparative study." IAES International Journal of Artificial Intelligence (IJ-AI) 14, no. 1 (2025): 702. http://dx.doi.org/10.11591/ijai.v14.i1.pp702-711.

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The Arabic language presents challenges for natural language processing (NLP) tasks. One such challenge is diacritization, which involves adding diacritical marks to Arabic text to enhance readability and disambiguation. Diacritics play a crucial role in determining the correct pronunciation, meaning, and grammatical structure of words and sentences. However, Arabic texts are often written without diacritics, making NLP tasks more complex. This study investigates the efficacy of advanced machine learning models in automatic Arabic text diacritization, with a concentrated focus on the Arabic bi

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Iman, Zubeiri, Souri Adnan, and Eddine El Mohajir Badr. "Arabic text diacritization using transformers: a comparative study." IAES International Journal of Artificial Intelligence (IJ-AI) 14, no. 1 (2025): 702–11. https://doi.org/10.11591/ijai.v14.i1.pp702-711.

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The Arabic language presents challenges for natural language processing (NLP) tasks. One such challenge is diacritization, which involves adding diacritical marks to Arabic text to enhance readability and disambiguation. Diacritics play a crucial role in determining the correct pronunciation, meaning, and grammatical structure of words and sentences. However, Arabic texts are often written without diacritics, making NLP tasks more complex. This study investigates the efficacy of advanced machine learning models in automatic Arabic text diacritization, with a concentrated focus on the Arabic bi

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de Voogt, Alex. "A Paleographic Analysis of Swahili-Arabic Script through Thirteen Poems." Journal of Islamic Manuscripts 16, no. 1 (2025): 97–113. https://doi.org/10.1163/1878464x-01601001.

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Abstract A paleographic analysis of a set of thirteen poems composed by Muyaka bin Haji (1776–1840) but written in Swahili-Arabic script by Mwalimu Sikujua in the 1890s reveals a consistent preference in the placement of script-specific diacritics and in the use of certain letterform combinations, but variation in the choice of graphic forms, particularly those for kāf. Sikujua places miniature consonant signs between a consonant letterform and a potential vowel diacritic. Since the miniature consonants are rendered in red, the scribe needs to alternate pens during the writing of the text or l

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Sabour, Adel, Abdeltawab Hendawi, and Mohamed Ali. "Arabic Diacritic-Aware Text-Audio Segmentation and Alignment Model (DASAM)." Elkawnie 10, no. 1 (2024): 1. http://dx.doi.org/10.22373/ekw.v10i1.23637.

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Abstract: This paper introduces the Diacritic-Aware Segmentation and Alignment Model for Arabic (DASAM). Diacritics are vital for pronunciation and meaning in the Arabic language but are often ignored by current speech recognition systems. DASAM is designed for word-level segmentation and alignment in unseen audio and associating them with diacritic-marked Arabic text. The DASAM approach uses linguistic analysis based on intonation rules. DASAM then applies Dynamic Time Warping (DTW) to match the reference audio word with its position in the unseen sentence audio. The model outputs a list of w

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Sattar Malik, Dr Abdul. "The Justification of Urdu Letters with Similar Sounds and Diacritics." Noor e Tahqeeq 8, no. 01 (2024): 109–18. http://dx.doi.org/10.54692/nooretahqeeq.2024.08012155.

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Urdu script is derived from the Arabic script but Urdu differs from Arabic in its nature and unlike Arabic some sounds are pronounced like each other. Due to that some experts object to Urdu script and suggest the removal of letters with similar sounds. But the removal of these letters can create many complexities and difficulties which cannot be resolved. These eight specific sounds of Urdu are common to Pakistani languages such as Punjabi, Sindhi, Pashto, Balochi, Kashmiri, and other local languages. How is it possible to exclude these words from all these languages? These sounds are the v

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Khoshafah, Saleh Abduh Naji Ali, and Ibraheem N. A. Tagaddeen. "Effect of Diacritics on Machine Translation Performance: A Case Study of Yemeni Literature." International Journal of Language and Literary Studies 5, no. 2 (2023): 324–42. http://dx.doi.org/10.36892/ijlls.v5i2.1342.

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Many Arabic texts are written without diacritics. However, in some contexts this raises the high level of homography and in turn presents difficulties for machine translation programs. Homographs are words which are spelled identically but have different meanings and are mostly pronounced differently. To avoid the problem of homography, words require to be diacriticized. Thus, the main objective of the study is to assess the ability of machine translation (henceforth MT) in rendering diacritical words from Arabic into English with special reference to translating Yemeni literature into English

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Khoshafah, Saleh Abduh Naji Ali, and Ibraheem N. A. Tagaddeen. "Effect of Diacritics on Machine Translation Performance: A Case Study of Yemeni Literature." International Journal of Language and Literary Studies 5, no. 2 (2023): 324–42. http://dx.doi.org/10.36892/ijlls.v5i2.1342.

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Many Arabic texts are written without diacritics. However, in some contexts this raises the high level of homography and in turn presents difficulties for machine translation programs. Homographs are words which are spelled identically but have different meanings and are mostly pronounced differently. To avoid the problem of homography, words require to be diacriticized. Thus, the main objective of the study is to assess the ability of machine translation (henceforth MT) in rendering diacritical words from Arabic into English with special reference to translating Yemeni literature into English

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12

Ahmed, Abdalla Sheikh, Sanusi Azmi Mohd, Abd Aziz Maslita, Nasser Al-Mhiqani Mohammed, and Saleh Bafjaish Salem. "Diacritic segmentation technique for arabic handwritten using region-based." Indonesian Journal of Electrical Engineering and Computer Science (IJEECS) 18, no. 1 (2020): 478–84. https://doi.org/10.11591/ijeecs.v18.i1.pp478-484.

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Arabic is a broadly utilized alphabetic composition framework on the planet, and it has 28 essential letters. The letters in order was first used to compose messages in Arabic, most prominently the Qur'an the holy book of Islam. However, Arabic language has diacritics in the word or letters which are not something extra or discretionary to the language, rather they are a vital piece of it. By changing some diacritics may change both the syntax and semantics of a word by turning a word into another. However, the current researches address the foreground image and consider the diacritics as

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13

Shiekh, Ahmed Abdalla, Mohd Sanusi Azmi, Maslita Abd Aziz, Mohammed Nasser Al-Mhiqani, and Salem Saleh Bafjaish. "Diacritic segmentation technique for arabic handwritten using region-based." Indonesian Journal of Electrical Engineering and Computer Science 18, no. 1 (2020): 478. http://dx.doi.org/10.11591/ijeecs.v18.i1.pp478-484.

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Arabic is a broadly utilized alphabetic composition framework on the planet, and it has 28 essential letters. The letters in order was first used to compose messages in Arabic, most prominently the Qur'an the holy book of Islam. However, Arabic language has diacritics in the word or letters which are not something extra or discretionary to the language, rather they are a vital piece of it. By changing some diacritics may change both the syntax and semantics of a word by turning a word into another. However, the current researches address the foreground image and consider the diacritics as nois

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14

Darwish, Kareem, Ahmed Abdelali, Hamdy Mubarak, and Mohamed Eldesouki. "Arabic Diacritic Recovery Using a Feature-rich biLSTM Model." ACM Transactions on Asian and Low-Resource Language Information Processing 20, no. 2 (2021): 1–18. http://dx.doi.org/10.1145/3434235.

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Diacritics (short vowels) are typically omitted when writing Arabic text, and readers have to reintroduce them to correctly pronounce words. There are two types of Arabic diacritics: The first are core-word diacritics (CW), which specify the lexical selection, and the second are case endings (CE), which typically appear at the end of word stems and generally specify their syntactic roles. Recovering CEs is relatively harder than recovering core-word diacritics due to inter-word dependencies, which are often distant. In this article, we use feature-rich recurrent neural network model that use a

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15

Bates, Michael L. "Arabic Diacritics without Special Software." Middle East Studies Association Bulletin 22, no. 1 (1988): 34–36. http://dx.doi.org/10.1017/s0026318400019519.

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16

Hifny, Yasser. "Open Vocabulary Arabic Diacritics Restoration." IEEE Signal Processing Letters 26, no. 10 (2019): 1421–25. http://dx.doi.org/10.1109/lsp.2019.2933721.

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Nazih, Waleed, and Yasser Hifny. "Arabic Syntactic Diacritics Restoration Using BERT Models." Computational Intelligence and Neuroscience 2022 (October 30, 2022): 1–8. http://dx.doi.org/10.1155/2022/3214255.

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The Arabic syntactic diacritics restoration problem is often solved using long short-term memory (LSTM) networks. Handcrafted features are used to augment these LSTM networks or taggers to improve performance. A transformer-based machine learning technique known as bidirectional encoder representations from transformers (BERT) has become the state-of-the-art method for natural language understanding in recent years. In this paper, we present a novel tagger based on BERT models to restore Arabic syntactic diacritics. We formulated the syntactic diacritics restoration as a token sequence classif

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18

Kurzon, Dennis. "A brief note on diacritics." Written Language and Literacy 11, no. 1 (2008): 90–94. http://dx.doi.org/10.1075/wll.11.1.07kur.

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This short note relates to remarks made by Peter Daniels in his 2006 article ‘On beyond alphabets’ on diacritics which he defines as markers that have a consistent phonological function in the particular script. From examples taken from French, Czech and other languages using the roman script, it is shown that the principal function of diacritics is to set up contrasts among various graphemes. This is extrapolated to the Arabic and Perso-Arabic scripts, where it is shown that the dots above and below graphemes are in effect diacritics.

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Alsayadi, Hamzah A., Abdelaziz A. Abdelhamid, Islam Hegazy, and Zaki T. Fayed. "Non-diacritized Arabic speech recognition based on CNN-LSTM and attention-based models." Journal of Intelligent & Fuzzy Systems 41, no. 6 (2021): 6207–19. http://dx.doi.org/10.3233/jifs-202841.

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Arabic language has a set of sound letters called diacritics, these diacritics play an essential role in the meaning of words and their articulations. The change in some diacritics leads to a change in the context of the sentence. However, the existence of these letters in the corpus transcription affects the accuracy of speech recognition. In this paper, we investigate the effect of diactrics on the Arabic speech recognition based end-to-end deep learning. The applied end-to-end approach includes CNN-LSTM and attention-based technique presented in the state-of-the-art framework namely, Espres

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Alshammari, Hamed, and Khaled Elleithy. "Toward Robust Arabic AI-Generated Text Detection: Tackling Diacritics Challenges." Information 15, no. 7 (2024): 419. http://dx.doi.org/10.3390/info15070419.

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Current AI detection systems often struggle to distinguish between Arabic human-written text (HWT) and AI-generated text (AIGT) due to the small marks present above and below the Arabic text called diacritics. This study introduces robust Arabic text detection models using Transformer-based pre-trained models, specifically AraELECTRA, AraBERT, XLM-R, and mBERT. Our primary goal is to detect AIGTs in essays and overcome the challenges posed by the diacritics that usually appear in Arabic religious texts. We created several novel datasets with diacritized and non-diacritized texts comprising up

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Huda, Kadhim Tayyeh, Salih Mahdi Mohammed, and Sabah Ahmed AL-Jumaili Ahmed. "Novel steganography scheme using Arabic text features in Holy Quran." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 3 (2019): 1910–18. https://doi.org/10.11591/ijece.v9i3.pp1910-1918.

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With the rapid growth of the Internet and mobile devices, the need for hidden communications has significantly increased. Steganography is a technique introduced for establishing hidden communication, Most steganography techniques have been applied to audio, images, videos, and text. Many researchers used steganography in Arabic texts to take advantage of adding, editing or changing letters or diacritics, but lead to notable and suspicious text. In this paper, we propose two novel steganography algorithms for Arabic text using the Holy Quran as cover text. The fact that it is forbidden to add,

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Kurzon, Dennis. "Diacritics and the Perso-Arabic script." Writing Systems Research 5, no. 2 (2013): 234–43. http://dx.doi.org/10.1080/17586801.2013.799451.

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Abed, Sa’ed, Mohammad Alshayeji, and Sari Sultan. "Diacritics Effect on Arabic Speech Recognition." Arabian Journal for Science and Engineering 44, no. 11 (2019): 9043–56. http://dx.doi.org/10.1007/s13369-019-04024-0.

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Tayyeh, Huda Kadhim, Mohammed Salih Mahdi, and Ahmed Sabah Ahmed AL-Jumaili. "Novel steganography scheme using Arabic text features in Holy Quran." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 3 (2019): 1910. http://dx.doi.org/10.11591/ijece.v9i3.pp1910-1918.

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<p>With the rapid growth of the Internet and mobile devices, the need for hidden communications has significantly increased. Steganography is a technique introduced for establishing hidden communication, Most steganography techniques have been applied to audio, images, videos, and text. Many researchers used steganography in Arabic texts to take advantage of adding, editing or changing letters or diacritics, but lead to notable and suspicious text. In this paper, we propose two novel steganography algorithms for Arabic text using the Holy Quran as cover text. The fact that it is forbidde

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Hallberg, Andreas. "Variation in the Use of Diacritics in Modern Typeset Standard Arabic: A Theoretical and Descriptive Framework." Arabica 69, no. 3 (2022): 279–317. http://dx.doi.org/10.1163/15700585-12341640.

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Abstract The extent to which the diacritic layer (taškīl) of the Arabic writing system is employed in modern typeset text differs considerably between genres and individual texts, with many in-between forms not aptly captured by the traditional binary categories of “vowelled” and “unvowelled” text. This article is the first to present a theoretical account of this variation applicable to modern typeset Standard Arabic. It is suggested that diacritics serve three basic functions: facilitation of reading comprehension; facilitation of prescriptively correct diction; and to evoke associations wit

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Subhi Shakir, Nooruldeen, and Mohammed Salih Mahdi. "USING SPECIAL LETTERS AND DIACRITICS IN STEGANOGRAPHY IN HOLY QURAN." Iraqi Journal for Computers and Informatics 49, no. 2 (2023): 1–8. http://dx.doi.org/10.25195/ijci.v49i2.417.

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Because of the great development that took place in information transfer and communication technologies, the issue of information transfer security has become a very sensitive and resonant issue, great importance must be given to protecting this confidential information. Steganography is one of the important and effective ways to protect the security of this information while it is being transmitted through the Internet, steganography is a technology to hide information inside an unnoticeable envelope object that can be an image, video, text or sound. The Arabic language has some special featu

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Mijlad, Ali, and Yacine El Younoussi. "A Comparative Study of Some Automatic Arabic Text Diacritization Systems." Advances in Human-Computer Interaction 2022 (August 16, 2022): 1–13. http://dx.doi.org/10.1155/2022/3613710.

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Arabic diacritization is the task of restoring diacritics or vowels for Arabic texts considering that they are mostly written without them. This task, when automated, shows better results for some natural language processing tasks; hence, it is necessary for the field of Arabic language processing. In this paper, we are going to present a comparative study of some automatic diacritization systems. One uses a variant of the hidden Markov model. The other one is a pipeline, which includes a Long Short-Term Memory deep learning model, a rule-based correction component, and a statistical-based com

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de Voogt, Alex. "Sikujua’s Writing of Muyaka’s Poetry in Arabic Script." Journal of Islamic Manuscripts 15, no. 1 (2023): 5–20. http://dx.doi.org/10.1163/1878464x-01401005.

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Abstract Muyaka’s poetry as it is known today was first recorded in the 1890s, mainly written down by Mwalimu Sikujua who used Arabic script as well as an adapted Swahili-Arabic writing system to document the language. Sikujua’s versatility when using the Arabic script as well as his use of variant spellings suggest a writing practice that embraces rather than avoids orthographic variation. His use of diacritics including the shadda and hamza is particularly noteworthy. Muyaka’s poems with their frequent repetitions as well as the writing of the poet’s name feature multiple spellings by Sikuju

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Abbad, Hamza, and Shengwu Xiong. "Simple Extensible Deep Learning Model for Automatic Arabic Diacritization." ACM Transactions on Asian and Low-Resource Language Information Processing 21, no. 2 (2022): 1–16. http://dx.doi.org/10.1145/3480938.

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Automatic diacritization is an Arabic natural language processing topic based on the sequence labeling task where the labels are the diacritics and the letters are the sequence elements. A letter can have from zero up to two diacritics. The dataset used was a subset of the preprocessed version of the Tashkeela corpus. We developed a deep learning model composed of a stack of four bidirectional long short-term memory hidden layers of the same size and an output layer at every level. The levels correspond to the groups that we classified the diacritics into (short vowels, double case-endings, Sh

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Zayyan, Ayman A., Mohamed Elmahdy, Husniza binti Husni, and Jihad Al Ja’am. "Automatic Diacritics Restoration for Dialectal Arabic Text." International Journal of Computing and Information Sciences 12, no. 2 (2016): 159–65. http://dx.doi.org/10.21700/ijcis.2016.119.

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Lutf, Mohammed, Xinge You, Yiu-ming Cheung, and C. L. Philip Chen. "Arabic font recognition based on diacritics features." Pattern Recognition 47, no. 2 (2014): 672–84. http://dx.doi.org/10.1016/j.patcog.2013.07.015.

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Hermena, Ehab W., Sana Bouamama, Simon P. Liversedge, and Denis Drieghe. "Does diacritics‐based lexical disambiguation modulate word frequency, length, and predictability effects? An eye‐movements investigation of processing Arabic diacritics." PLOS ONE 16, no. 11 (2021): e0259987. http://dx.doi.org/10.1371/journal.pone.0259987.

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In Arabic, a predominantly consonantal script that features a high incidence of lexical ambiguity (heterophonic homographs), glyph-like marks called diacritics supply vowel information that clarifies how each consonant should be pronounced, and thereby disambiguate the pronunciation of consonantal strings. Diacritics are typically omitted from print except in situations where a particular homograph is not sufficiently disambiguated by the surrounding context. In three experiments we investigated whether the presence of disambiguating diacritics on target homographs modulates word frequency, le

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Abdelkader, Drissi Otmane, Sane Mohamed Yagi, and Majdi Shaker Sawalha. "Sources of Syntactic Ambiguity in Contemporary Arabic: A Corpus Study." Jordanian Educational Journal 9, no. 3 (2024): 27–46. https://doi.org/10.46515/jaes.v9i3.869.

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Recently, Arabic began gaining ground in the area of research within Natural Language Processing (NLP). This study constructs a syntactically annotated corpus based on the framework of I3rab to discuss the sources of syntactic ambiguities in Contemporary Arabic. The corpus of this study is a sub-corpus of the Jordan Comprehensive Contemporary Arabic Corpus (JCCA). It contains over 100000 words gathered from different written and spoken texts. Annotation involves manually adding the grammatical function of each word in its immediate context. Findings show that Contemporary Arabic exhibits diffe

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Alkhudaydi, Malak G., and Adnan A. Gutub. "Integrating Light-Weight Cryptography with Diacritics Arabic Text Steganography Improved for Practical Security Applications." Journal of Information Security and Cybercrimes Research 3, no. 1 (2020): 13–30. http://dx.doi.org/10.26735/fmit1649.

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Cryptography and steganography are combined to provide practical data security. This paper proposes integrating light-weight cryptography with improved Arabic text steganography for optimizing security applications. It uses light-weight cryptography to cope with current limited device capabilities, to provide acceptable required security. The work tests hiding encrypted secret information within Arabic stego-cover texts, using all common diacritics found naturally in the Arabic language. The study considers different challenging situations and scenarios in order to evaluate security practicali

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Rawaa, Hamza Ali, Nadeem Dhannoon Ban, and Iedan Hamel Mohammed. "Arabic text steganography using lunar and solar diacritics." Arabic text steganography using lunar and solar diacritics 31, no. 3 (2023): 1559–67. https://doi.org/10.11591/ijeecs.v31.i3.pp1559-1567.

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The need to hide essential information has rapidly increased as mobile devices and the internet has overgrown. Steganography is a method created to create hidden communication. Recently, methods have been developed to hide important information using text steganography. This work-study takes advantage of the possibility of concealing data in all diacritics after the two letters )ال (in the cover text. In the presented study, we propose a new algorithm in steganography in Arabic text as a cover text. After pre-processing the cover text, the algorithm hides the elements of secret messages inside

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Hssini, Mohamed. "Problem of Multiple Diacritics Design for Arabic Script." IOSR Journal of Engineering 02, no. 12 (2012): 48–53. http://dx.doi.org/10.9790/3021-021234853.

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Ali, Rawaa Hamza, Ban Nadeem Dhannoon, and Mohamed Iedan Hamel. "Arabic text steganography using lunar and solar diacritics." Indonesian Journal of Electrical Engineering and Computer Science 31, no. 3 (2023): 1559. http://dx.doi.org/10.11591/ijeecs.v31.i3.pp1559-1567.

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The need to hide essential information has rapidly increased as mobile devices and the internet has overgrown. Steganography is a method created to create hidden communication. Recently, methods have been developed to hide important information using text steganography. This work-study takes advantage of the possibility of concealing data in all diacritics after the two letters <em>ال</em>)<em>)</em> in the cover text. In the presented study, we propose a new algorithm in steganography in Arabic text as a cover text. After pre-processing the cover text, the algorithm hi

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Hifny, Yasser. "Hybrid LSTM/MaxEnt Networks for Arabic Syntactic Diacritics Restoration." IEEE Signal Processing Letters 25, no. 10 (2018): 1515–19. http://dx.doi.org/10.1109/lsp.2018.2865098.

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Bourisly, Ali K., Charles Haynes, Nibal Bourisly, and Maria Mody. "Neural correlates of diacritics in Arabic: An fMRI study." Journal of Neurolinguistics 26, no. 1 (2013): 195–206. http://dx.doi.org/10.1016/j.jneuroling.2012.07.004.

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Al-anzi, Fawaz S. "Stochastic Models for Automatic Diacritics Generation of Arabic Names." Computers and the Humanities 38, no. 4 (2004): 469–81. http://dx.doi.org/10.1007/s10579-004-2323-6.

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Youssef, Nahla Ibrahim, and Nadia Abd-Alsabour. "A REVIEW ON ARABIC HANDWRITING RECOGNITION." Journal of Southwest Jiaotong University 57, no. 6 (2022): 745–64. http://dx.doi.org/10.35741/issn.0258-2724.57.6.66.

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Handwriting recognition is considered a very hard area of research, especially for Arabic, because of its ligatures, cursive nature, diacritics, and overlapping. Although many studies have been conducted on Arabic recognition, this field still has many unsolved problems. This work aims to provide a comprehensive review of various strategies for handling Arabic handwriting recognition. Furthermore, it details handwriting recognition, general recognition, Arabic recognition, its characteristics, and the difficulties it faces. Additionally, we discuss online and offline Arabic recognition and oth

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Marcet, Ana, Hnazand Ghukasyan, María Fernández-López, and Manuel Perea. "Jalapeno or jalapeño: Do diacritics in consonant letters modulate visual similarity effects during word recognition?" Applied Psycholinguistics 41, no. 3 (2020): 579–93. http://dx.doi.org/10.1017/s0142716420000090.

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AbstractPrior research has shown that word identification times to DENTIST are faster when briefly preceded by a visually similar prime (dentjst; i↔j) than when preceded by a visually dissimilar prime (dentgst). However, these effects of visual similarity do not occur in the Arabic alphabet when the critical letter differs in the diacritical signs: for the target the visually similar one-letter replaced prime (compare and is no more effective than the visually dissimilar one-letter replaced prime Here we examined whether this dissociative pattern is due to the special role of diacritics during

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Lamghari, N., and S. Raghay. "Recognition of Arabic Handwritten Diacritics using the new database DBAHD." Journal of Physics: Conference Series 1743 (January 2021): 012023. http://dx.doi.org/10.1088/1742-6596/1743/1/012023.

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Mohammad, Khader, Aziz Qaroush, Muna Ayesh, Mahdi Washha, Ahmad Alsadeh, and Sos Agaian. "Contour-based character segmentation for printed Arabic text with diacritics." Journal of Electronic Imaging 28, no. 04 (2019): 1. http://dx.doi.org/10.1117/1.jei.28.4.043030.

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Boudelaa, Sami, Dennis Norris, and Sachiko Kinoshita. "The differential effects of consonant and vowel diacritics in Arabic." Journal of Memory and Language 138 (October 2024): 104533. http://dx.doi.org/10.1016/j.jml.2024.104533.

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Can, Yekta Said, and M. Erdem Kabadayı. "Automatic CNN-Based Arabic Numeral Spotting and Handwritten Digit Recognition by Using Deep Transfer Learning in Ottoman Population Registers." Applied Sciences 10, no. 16 (2020): 5430. http://dx.doi.org/10.3390/app10165430.

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Historical manuscripts and archival documentation are handwritten texts which are the backbone sources for historical inquiry. Recent developments in the digital humanities field and the need for extracting information from the historical documents have fastened the digitization processes. Cutting edge machine learning methods are applied to extract meaning from these documents. Page segmentation (layout analysis), keyword, number and symbol spotting, handwritten text recognition algorithms are tested on historical documents. For most of the languages, these techniques are widely studied and h

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Shakir, Ahmed Chalak, Gu Xuemai, and Jia Min. "Chinese Language Steganography using the Arabic Diacritics as a Covered Media." International Journal of Computer Applications 11, no. 1 (2010): 43–46. http://dx.doi.org/10.5120/1543-2050.

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Ayesh, Muna, Khader Mohammad, Aziz Qaroush, Sos Agaian, and Mahdi Washha. "A Robust Line Segmentation Algorithm for Arabic Printed Text with Diacritics." Electronic Imaging 2017, no. 13 (2017): 42–47. http://dx.doi.org/10.2352/issn.2470-1173.2017.13.ipas-204.

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Hamed, Osama, and Torsten Zesch. "The Role of Diacritics in Designing Lexical Recognition Tests for Arabic." Procedia Computer Science 117 (2017): 119–28. http://dx.doi.org/10.1016/j.procs.2017.10.100.

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Chennoufi, Amine, and Azzeddine Mazroui. "Morphological, syntactic and diacritics rules for automatic diacritization of Arabic sentences." Journal of King Saud University - Computer and Information Sciences 29, no. 2 (2017): 156–63. http://dx.doi.org/10.1016/j.jksuci.2016.06.004.

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