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Comparative evaluation of tools for Arabic corpora search and analysis
2015
International Journal of Speech Technology
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Article: Alfaifi, A and Atwell, ES orcid.org/0000-0001-9395-3764 (2016) Comparative evaluation of tools for Arabic corpora search and analysis. ...
of the Arabic language, and provides users with a greater number of functions. ...
comments and suggestions to improve the quality of the paper. ...
doi:10.1007/s10772-015-9285-5
fatcat:hp3slx2d55dj5agefgnvfb4fua
Arabic Text Diacritization Using Deep Neural Networks
[article]
2019
arXiv
pre-print
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Diacritization of Arabic text is both an interesting and a challenging problem at the same time with various applications ranging from speech synthesis to helping students learning the Arabic language. ...
The results of the experiments show that the neural Shakkala system significantly outperforms traditional rule-based approaches and other closed-source tools with a Diacritic Error Rate (DER) of 2.88% ...
Moreover, we provide a critical review for the currently existing systems and tools for Arabic text diacritization and perform an empirical study to compare the performance of six of them on our dataset ...
arXiv:1905.01965v1
fatcat:4epouzf7hrgxrgcjvi6o5jl66i
Arabic Morphological Analysis Techniques
2020
International Journal of Advanced Computer Science and Applications
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This paper aims to survey Arabic morphological analysis techniques from 2005 to 2019 and to organize them into a reasonable and expandable classification system. ...
There are many scientific studies on Arabic morphological analysis, yet most of them lack an accurate classification of Arabic morphology and fail to cover both recent and traditional techniques. ...
In the fourth section, we present a survey of Arabic morphological analysis techniques. The fifth section presents a discussion of the comparative study undertaken. ...
doi:10.14569/ijacsa.2020.0110229
fatcat:4q3brmcldzbidbbtjtqa3rsgby
Design of Arabic Diacritical Marks
[article]
2011
arXiv
pre-print
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This paper aims to study the placement and sizing of diacritical marks in Arabic script, with a comparison with the Latin's case. ...
In the beginning, we compare the difficulty of processing diacritics in both scripts. After, we will study the limits of Latin resolution strategies when applied to Arabic. ...
The problem must be studied in a more systematic approach by basing itself on a study concerning the choice of the sizes of diacritical marks and their positions. ...
arXiv:1107.4734v1
fatcat:slf7o6eec5hajb465zfgf72fbe
Arabic Diacritic Recovery Using a Feature-Rich biLSTM Model
[article]
2020
arXiv
pre-print
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Our model surpasses all previous state-of-the-art systems with a CW error rate (CWER) of 2.86\% and a CE error rate (CEER) of 3.7% for Modern Standard Arabic (MSA) and CWER of 2.2% and CEER of 2.5% for ...
In this paper, we use a feature-rich recurrent neural network model that uses a variety of linguistic and surface-level features to recover both core word diacritics and case endings. ...
Reliable NLP tools may be required to generate some of these features, and such tools may not be readily available for other language varieties, such as dialectal Arabic. ...
arXiv:2002.01207v1
fatcat:gvgzwhkws5hf3drqshxfzjxlvi
A Hybrid Approach for the Morpho-Lexical Disambiguation of Arabic
2016
Journal of Information Processing Systems
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This hybrid approach combines a linguistic approach with a multi-criteria decision one and could be considered as an alternative choice to solve the morpho-lexical ambiguity problem regardless of the diacritics ...
As to its evaluation, we tried the disambiguation on the online Alkhalil morphological analyzer (the proposed approach can be used on any morphological analyzer of the Arabic language) and obtained encouraging ...
Given the significant proportion of ambiguous words that have resulted from the developed tools and methods, we can conclude that, for Arabic, this phenomenon is very common and requires further study. ...
doi:10.3745/jips.02.0041
fatcat:halr2rlgtzce5brldq42ynvmai
A new framework for Arabic recitation using speech recognition and the Jaro Winkler algorithm
2021
Maǧallaẗ Al-Kuwayt li-l-ʿulūm
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To validate the obtained results, two comparison studies were performed. The Jaro Winker distance was successfully compared to the cosine and the Euclidean distance. ...
This article proposed a new system (Samee'a - ) to facilitate memorizing any kind of text such that poems, speeches and the Holy Qur'an. ...
ACKNOWLEDGEMENTS The authors would like to acknowledge the support of prince sultan university. ...
doi:10.48129/kjs.v49i1.11231
fatcat:uo7ddxfpmngwvdn4ckraff4yh4
Collecting Data for Automatic Speech Recognition Systems in Dialectal Arabic Using Games with a Purpose
[chapter]
2015
Lecture Notes in Computer Science
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In this paper, we introduce Games With a Purpose as a cheap and fast approach to gather transcriptions for Egyptian dialectal Arabic. ...
On the other hand, transcriptions written in Arabic Chat Alphabet are widely used, and include the pronunciation effects given by diacritics. ...
Survey results Highest Verification is calculated by counting the number of repeated Arabic and Franco transcription for a given audio-file . ...
doi:10.1007/978-3-319-15557-9_10
fatcat:ygbeovgpgjefpihhtiphirbf4e
Neural Arabic Text Diacritization: State of the Art Results and a Novel Approach for Machine Translation
2019
Proceedings of the 6th Workshop on Asian Translation
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2019 pre-print arXiv:1911.03531v1 fatcat:vtktt7xy2zdqlb2b37wxyf3edq
In this work, we present several deep learning models for the automatic diacritization of Arabic text. Our models are built using two main approaches, viz. ...
Moreover, we show that diacritics in Arabic can be used to enhance the models of NLP tasks such as Machine Translation (MT) by proposing the Translation over Diacritization (ToD) approach. ...
Acknowledgments We gratefully acknowledge the support of the Deanship of Research at the Jordan University of Science and Technology for supporting this work via Grant #20180193 in addition to NVIDIA Corporation ...
doi:10.18653/v1/d19-5229
dblp:conf/aclwat/FadelTAA19
fatcat:2juysnbqx5c33nckj526me4sxa
A Survey of Arabic language Support in Semantic web
2010
International Journal of Computer Applications
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This highly digitalized result of technological advancement is dedicated to processing Latin family scripts but the studies that deal with Arabic script support in these technologies remained silent and ...
This paper, therefore, would like to account the support of Arabic in some of the existing Semantic Web technologies, and determine the ability to applying Semantic Web for Arabic applications. ...
In this study, the evaluated tools like the Protégé and Jena, Sesame, and KOAN resulted to weak support of the Arabic language and thus, the need for new tools supporting ARABIC NLP is crucial. ...
doi:10.5120/1348-1818
fatcat:4h4ala5sy5eubpus3d4zfwxota
A survey of arabic text classification models
2019
International Journal of Informatics and Communication Technology (IJ-ICT)
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This paper is a survey of Arabic text classification. ...
As a result, these problems represent challenges in the classification, and organization of specific Arabic text. ...
ACKNOWLEDGEMENTS We would like to thank Al Hussein bin Talal University (AHU) for providing us a good scientific environment to produce this simple work. ...
doi:10.11591/ijict.v8i1.pp25-28
fatcat:63xz4adhfrcgdcg3uv2totl22q
A Survey of Arabic Text Classification Models
2018
International Journal of Electrical and Computer Engineering (IJECE)
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This paper is a survey of Arabic text classification. ...
As a result, these problems represent challenges in the classification, and organization of specific Arabic text. ...
ACKNOWLEDGEMENT We would like to thank Al_Hussein bin Talal University (AHU) for providing us a good scientific environment to produce this simple work. ...
doi:10.11591/ijece.v8i6.pp4352-4355
fatcat:lb3mrcumgjhrxdjzm6wxyef34e
arTenTen: Arabic Corpus and Word Sketches
2014
Journal of King Saud University: Computer and Information Sciences
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A chunk of it has been lemmatized and part-of-speech (POS) tagged with the MADA tool and subsequently loaded into Sketch Engine, a leading corpus query tool, where it is open for all to use. ...
We present arTenTen, a web-crawled corpus of Arabic, gathered in 2012. arTenTen consists of 5.8-billion words. ...
Acknowledgments This work was partly supported by the Ministry of Education of the Czech Republic within the LINDAT-Clarin project LM2010013 and by the Ministry of the Interior of the Czech Republic within ...
doi:10.1016/j.jksuci.2014.06.009
fatcat:u37zwv6hefhkrauxggupohpzs4
Decision Support System Tool for Arabic Text Recognition
2021
Intelligent Automation and Soft Computing
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Therefore, this study aims to overcome these issues by developing a decision support tool called TiMELY for automatic Arabic text recognition using artificial intelligence techniques. ...
We applied a comparative approach in selecting the highest score using three Arabic text extraction algorithms: term frequency-inverse document frequency measure algorithm, Cortical.io tool with Retina ...
Table 1 : 1 Examples of Arabic diacritic complexities # Word with Transcription Diacritic position and type Example diacritics in Arabic with the letter La:m 1 ﻒ ﺃ َ ﻟ ِ A-li-fØ Kasra underneath ...
doi:10.32604/iasc.2021.014828
fatcat:2mqq3m5ts5htzpfyorrp2ayrhy
ArCADE: An Arabic Corpus of Auditory Dictation Errors
2014
Proceedings of the Ninth Workshop on Innovative Use of NLP for Building Educational Applications
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The corpus may be useful to instructors of Arabic as a second language, and researchers who study second language phonology and listening perception. ...
We present a new corpus of word-level listening errors collected from 62 native English speakers learning Arabic designed to inform models of spell checking for this learner population. ...
Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the University of Maryland, College Park and/or ...
doi:10.3115/v1/w14-1813
dblp:conf/bea/RyttingRBNBSM14
fatcat:gduipeapbfebbg4vydmvt6qpvm
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