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2. Optimizing Arabic Text Readability Measurement Using Morphological Word Embeddings

Author

Berrichi, Safae, Nassiri, Naoual, Mazroui, Azzeddine, Lakhouaja, Abdelhak, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Elhadj, Yahya Mohamed, editor, Nanne, Mohamedade Farouk, editor, Koubaa, Anis, editor, Meziane, Farid, editor, and Deriche, Mohamed, editor

Published
2024
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3. Exploring the Impact of Deep Learning Techniques on Evaluating Arabic L1 Readability

Author

Berrichi, Safae, Nassiri, Naoual, Mazroui, Azzeddine, Lakhouaja, Abdelhak, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Farhaoui, Yousef, editor, Hussain, Amir, editor, Saba, Tanzila, editor, Taherdoost, Hamed, editor, and Verma, Anshul, editor

Published
2024
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4. Lexical Simplification of Arabic Educational Texts Through a Classification Approach

Author

Nassiri, Naoual, Berrichi, Safae, Lakhouaja, Abdelhak, Cavalli-Sforza, Violetta, Mazroui, Azzeddine, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Farhaoui, Yousef, editor, Rocha, Alvaro, editor, Brahmia, Zouhaier, editor, and Bhushab, Bharat, editor

Published
2023
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5. Impact of Feature Vectorization Methods on Arabic Text Readability Assessment

Author

Berrichi, Safae, Nassiri, Naoual, Mazroui, Azzeddine, Lakhouaja, Abdelhak, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Farhaoui, Yousef, editor, Rocha, Alvaro, editor, Brahmia, Zouhaier, editor, and Bhushab, Bharat, editor

Published
2023
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6. Combining Classical and Non-classical Features to Improve Readability Measures for Arabic First Language Texts

Author

Nassiri, Naoual, Lakhouaja, Abdelhak, Cavalli-Sforza, Violetta, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Balas, Valentina E., editor, and Ezziyyani, Mostafa, editor

Published
2022
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14. A Comparative Study of Standard Part-of-Speech Taggers

Author

Zeroual, Imad, Lakhouaja, Abdelhak, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, and Ezziyyani, Mostafa, editor

Published
2019
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15. Developing Effective Educative Games for Arabic Children Primarily Dyslexics

Author

El Kah, Anoual and Lakhouaja, Abdelhak

Abstract

Since the early stages of schooling, many children are exposed to different learning disabilities, usually manifest as dyslexia, dysgraphia, and dyscalculia. Those disabilities impact on the normal academic achievement of the child and may even affect its social life. Learning disorders have neurobiological origins and are often inherited regardless of the geographical region or the socio-economic status. It should not be seen as physical disorders (visual or hearing handicaps or mental retardation). They are simply a different way of acquiring new knowledge and skills. Learning disabled children only require an early intervention, adjustments in the teaching process, and compensatory efficient strategies. They need more encounters with words and more practice and revision opportunities. For the reason to follow the normal academic achievement process, either manual or electronic tools have been introduced to help children with learning disabilities (LD). Our contribution is a set of games for children with dyslexia and dysgraphia. The games delicately target Arabic learning disabilities and lend a helping hand to the child with LD to overcome his/her reading and writing complications. This set of games is evaluated and tested by 46 pupils, aged from seven to nine years old, from whom 20 pupils are considered as individuals with learning problems in general and 5 students determined as dyslexics. The results statistically reflect the system's efficiency and its distinctive role in improving the learning process.

Published
2018
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16. Integrating Corpus-Based Analyses in Language Teaching and Learning: Challenges and Guidelines

Author

Zeroual, Imad, El Kah, Anoual, Lakhouaja, Abdelhak, Barbosa, Simone Diniz Junqueira, Series Editor, Filipe, Joaquim, Series Editor, Kotenko, Igor, Series Editor, Sivalingam, Krishna M., Series Editor, Washio, Takashi, Series Editor, Yuan, Junsong, Series Editor, Zhou, Lizhu, Series Editor, Tabii, Youness, editor, Lazaar, Mohamed, editor, Al Achhab, Mohammed, editor, and Enneya, Nourddine, editor

Published
2018
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17. Modern Standard Arabic Readability Prediction

Author

Nassiri, Naoual, Lakhouaja, Abdelhak, Cavalli-Sforza, Violetta, Barbosa, Simone Diniz Junqueira, Series editor, Chen, Phoebe, Series editor, Filipe, Joaquim, Series editor, Kotenko, Igor, Series editor, Sivalingam, Krishna M., Series editor, Washio, Takashi, Series editor, Yuan, Junsong, Series editor, Zhou, Lizhu, Series editor, Lachkar, Abdelmonaime, editor, Bouzoubaa, Karim, editor, Mazroui, Azzedine, editor, Hamdani, Abdelfettah, editor, and Lekhouaja, Abdelhak, editor

Published
2018
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19. Arabic Readability Assessment for Foreign Language Learners

Author

Nassiri, Naoual, Lakhouaja, Abdelhak, Cavalli-Sforza, Violetta, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Weikum, Gerhard, Series Editor, Silberztein, Max, editor, Atigui, Faten, editor, Kornyshova, Elena, editor, Métais, Elisabeth, editor, and Meziane, Farid, editor

Published
2018
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34. MulTed: a multilingual aligned and tagged parallel corpus.

Author

Zeroual, Imad and Lakhouaja, Abdelhak

Subjects
MACHINE translating, NATURAL language processing, CORPORA, PARTS of speech
Abstract

Recently, more data-driven approaches are demanding multilingual parallel resources primarily in the crosslanguage studies. To meet these demands, building multilingual parallel corpora are becoming the focus of many Natural Language Processing (NLP) scientific groups. Unlike monolingual corpora, the number of available multilingual parallel corpora is limited. In this paper, the MulTed, a corpus of subtitles extracted from TEDx talks is introduced. It is multilingual, Part of Speech (PoS) tagged, and bilingually sentence-aligned with English as a pivot language. This corpus is designed for many NLP applications, where the sentencealignment, the PoS tagging, and the size of corpora are influential such as statistical machine translation, language recognition, and bilingual dictionary generation. Currently, the corpus has subtitles that cover 1100 talks available in over 100 languages. The subtitles are classified based on a variety of topics such as Business, Education, and Sport. Regarding the PoS tagging, the Treetagger, a language-independent PoS tagger, is used; then, to make the PoS tagging maximally useful, a mapping process to a universal common tagset is performed. Finally, we believe that making the MulTed corpus available for a public use can be a significant contribution to the literature of NLP and corpus linguistics, especially for under-resourced languages. [ABSTRACT FROM AUTHOR]

Published
2022
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37. MoSAR

Author

Nassiri, Naoual, primary, Cavalli-Sforza, Violetta, additional, and Lakhouaja, Abdelhak, additional

Published
2019
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39. Adapting a decision tree based tagger for Arabic

Author

Lakhouaja Abdelhak and Zeroual Imad

Subjects
business.industry, Arabic, Computer science, Speech recognition, Lemmatisation, Decision tree, 02 engineering and technology, computer.software_genre, Part of speech, language.human_language, 030507 speech-language pathology & audiology, 03 medical and health sciences, 0202 electrical engineering, electronic engineering, information engineering, language, Modern Standard Arabic, 020201 artificial intelligence & image processing, Artificial intelligence, Language model, 0305 other medical science, Hidden Markov model, business, Classical Arabic, computer, Natural language processing, Lemma (morphology)
Abstract

Several probabilistic methods used for Part of speech (POS) tagging are based on Hidden Markov Models (HMM), these methods have difficulties especially in estimating transition probabilities accurately from limited amounts of training data. Consequently, a new method appeared to avoid problems that HMM face. However, the transition probabilities are estimated using a decision tree. Based on this method a language independent POS tagger (called TreeTagger) has been implemented. The main purpose of this work is to create the language model to adapt TreeTagger for Arabic POS tagging and lemmatization. Furthermore, different configurations have been done, namely, collecting lexical resources, as well as the annotated training corpora. In addition, we used the proposed universal tagset that consists of common POS categories of 22 different languages including Arabic. We highlight the use of this tagger via various experiments on vowelled and unvowelled text from both Modern Standard Arabic and Classical Arabic. In fact, the obtained accuracies rates are 99.4%, 92.6% and 81.9% for respectively the Quranic vowelled corpus "Al-Mus'haf", the unvowelled "Al-Mus'haf1" corpus and for the NEMLAR corpus.

Published
2016
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45. Hybrid approaches for automatic vowelization of Arabic texts

Author

Lakhouaja Abdelhak, Mazroui Azzeddine, Chennoufi Amine, and Mohamed Bebah

Subjects
FOS: Computer and information sciences, Computer Science - Computation and Language, biology, Process (engineering), business.industry, Computer science, 68T50, Context (language use), Morpho, Viterbi algorithm, computer.software_genre, Lexical database, biology.organism_classification, symbols.namesake, Path (graph theory), symbols, Artificial intelligence, business, Hidden Markov model, Computation and Language (cs.CL), computer, Natural language processing, Word (computer architecture)
Abstract

Hybrid approaches for automatic vowelization of Arabic texts are presented in this article. The process is made up of two modules. In the first one, a morphological analysis of the text words is performed using the open source morphological Analyzer AlKhalil Morpho Sys. Outputs for each word analyzed out of context, are its different possible vowelizations. The integration of this Analyzer in our vowelization system required the addition of a lexical database containing the most frequent words in Arabic language. Using a statistical approach based on two hidden Markov models (HMM), the second module aims to eliminate the ambiguities. Indeed, for the first HMM, the unvowelized Arabic words are the observed states and the vowelized words are the hidden states. The observed states of the second HMM are identical to those of the first, but the hidden states are the lists of possible diacritics of the word without its Arabic letters. Our system uses Viterbi algorithm to select the optimal path among the solutions proposed by Al Khalil Morpho Sys. Our approach opens an important way to improve the performance of automatic vowelization of Arabic texts for other uses in automatic natural language processing., 19 pages

Published
2014

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