Search results for: stimulus Arabic words

Authors: Faaza A, Almarsoomi, James D, O'Shea, Zuhair A, Bandar, Keeley A, Crockett

Abstract:

This paper is concerned with the production of an Arabic word semantic similarity benchmark dataset. It is the first of its kind for Arabic which was particularly developed to assess the accuracy of word semantic similarity measurements. Semantic similarity is an essential component to numerous applications in fields such as natural language processing, artificial intelligence, linguistics, and psychology. Most of the reported work has been done for English. To the best of our knowledge, there is no word similarity measure developed specifically for Arabic. In this paper, an Arabic benchmark dataset of 70 word pairs is presented. New methods and best possible available techniques have been used in this study to produce the Arabic dataset. This includes selecting and creating materials, collecting human ratings from a representative sample of participants, and calculating the overall ratings. This dataset will make a substantial contribution to future work in the field of Arabic WSS and hopefully it will be considered as a reference basis from which to evaluate and compare different methodologies in the field.

Keywords: Arabic categories, benchmark dataset, semantic similarity, word pair, stimulus Arabic words

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Authors: Jawad H AlKhateeb, Jianmin Jiang, Jinchang Ren, Stan S Ipson

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Efficient preprocessing is very essential for automatic recognition of handwritten documents. In this paper, techniques on segmenting words in handwritten Arabic text are presented. Firstly, connected components (ccs) are extracted, and distances among different components are analyzed. The statistical distribution of this distance is then obtained to determine an optimal threshold for words segmentation. Meanwhile, an improved projection based method is also employed for baseline detection. The proposed method has been successfully tested on IFN/ENIT database consisting of 26459 Arabic words handwritten by 411 different writers, and the results were promising and very encouraging in more accurate detection of the baseline and segmentation of words for further recognition.

Keywords: Arabic OCR, off-line recognition, Baseline estimation, Word segmentation.

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Authors: Z. Shaaban

Abstract:

This paper presents a new approach to tackle the problem of recognizing machine-printed Arabic texts. Because of the difficulty of recognizing cursive Arabic words, the text has to be normalized and segmented to be ready for the recognition stage. The new scheme for recognizing Arabic characters depends on multiple parallel neural networks classifier. The classifier has two phases. The first phase categories the input character into one of eight groups. The second phase classifies the character into one of the Arabic character classes in the group. The system achieved high recognition rate.

Keywords: Neural Networks, character recognition, feature extraction, multiple networks, Arabic text.

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Authors: May George

Abstract:

Inference plays an important role in the learning process and it can lead to a rapid acquisition of a second language. When learning a non-native language i.e., a critical language like Arabic, the students depend on the teacher’s support most of the time to learn new concepts. The students focus on memorizing the new vocabulary and stress on learning all the grammatical rules. Hence, the students became mechanical and cannot produce the language easily. As a result, they are unable to predicate the meaning of words in the context by relying heavily on the teacher, in that they cannot link their prior knowledge or even identify the meaning of the words without the support of the teacher. This study explores how the teacher guides students learning during the inference process and what are the processes of learning that can direct student’s inference.

Keywords: Inference, Reading, Arabic, and Language Acquisition.

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Authors: Hana Almakky, Reza Sahandi, Jacqui Taylor

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Social media continues to grow, and user interfaces may become more appealing if cultural characteristics are incorporated into their design. Facebook was designed in the west, and the original language was English. Subsequently, the words in the user interface were translated to other languages, including Arabic. Arabic words are written from right to left, and English is written from left to right. The translated version may misrepresent the original design and users’ preferences may be influenced by their culture, which should be considered in the user interface design. Previous research indicates that users are more comfortable when interacting with a user interface, which relates to their own culture. Therefore, this paper, using a survey, investigates the preferences of Saudi Arabians on the Arabic version of the user interface of Facebook.

Keywords: Culture, Facebook, Saudi Arabia, Social media, User Interface Design.

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Authors: Osama Abufanas

Abstract:

This paper aims to build an Arabic learning language tool using Flash CS4 professional software with action script 3.0 programming language, based on the Computer Aided Language Learning (CALL) material. An extra intention is to provide a primary tool and focus on learning Arabic as a second language to adults. It contains letters, words and sentences at the first stage. This includes interactive practices, which evaluates learners’ comprehension of the Arabic language. The system was examined and it was found that the language structure was correct and learners were satisfied regarding the system tools. The learners found the system tools efficient and simple to use. The paper's main conclusion illustrates that CALL can be applied without any hesitation to second language learners

Keywords: Arabic Language, Computer Aided Language Learning (CALL), Learner, Material.

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Authors: Randa Ibrahim Elanwar, Mohsen Rashwan, Samia Mashali

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In this paper we propose a segmentation system for unconstrained Arabic online handwriting. An essential problem addressed by analytical-based word recognition system. The system is composed of two-stages the first is a newly special designed hidden Markov model (HMM) and the second is a rules based stage. In our system, handwritten words are broken up into characters by simultaneous segmentation-recognition using HMMs of unique design trained using online features most of which are novel. The HMM output characters boundaries represent the proposed segmentation points (PSP) which are then validated by rules-based post stage without any contextual information help to solve different segmentation errors. The HMM has been designed and tested using a self collected dataset (OHASD) [1]. Most errors cases are cured and remarkable segmentation enhancement is achieved. Very promising word and character segmentation rates are obtained regarding the unconstrained Arabic handwriting difficulty and not using context help.

Keywords: Arabic, Hidden Markov Models, online handwriting, word segmentation

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Authors: Ibrahim A. El rube, Mohamed T. El Sonni, Soha S. Saleh

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the cursive nature of the Arabic writing makes it difficult to accurately segment characters or even deal with the whole word efficiently. Therefore, in this paper, a printed Arabic sub-word recognition system is proposed. The suggested algorithm utilizes geometrical moments as descriptors for the separated sub-words. Three types of moments are investigated and applied to the printed sub-word images after dividing each image into multiple parts using windowing. Since moments are global descriptors, the windowing mechanism allows the moments to be applied to local regions of the sub-word. The local-global mixture of the proposed scheme increases the discrimination power of the moments while keeping the simplicity and ease of use of moments.

Keywords: Arabic sub-word recognition, windowing, aspectratio, moments.

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Authors: Sherif Abdelazeem

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A comparison between the performance of Latin and Arabic handwritten digits recognition problems is presented. The performance of ten different classifiers is tested on two similar Arabic and Latin handwritten digits databases. The analysis shows that Arabic handwritten digits recognition problem is easier than that of Latin digits. This is because the interclass difference in case of Latin digits is smaller than in Arabic digits and variances in writing Latin digits are larger. Consequently, weaker yet fast classifiers are expected to play more prominent role in Arabic handwritten digits recognition.

Keywords: Handwritten recognition, Arabic recognition, Digits recognition, Document recognition

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Authors: Y.M. Paltore, B.N. Zhubatova, A.A. Mustafayeva

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Abai Kunanbayev is famous for being enlightener, composer, interpreter, social agent, philosopher, reformer, who wanted to enrich Kazakh literature by emergence with Russian and European culture, and also as a founder of Kazakh written literary language. Abai Kunanbayev was born in 1845 in East Kazakhstan area and passed away in 1904 in his hometown. His oeuvre absorbed and reflected all changes in the life of Kazakh society of the second half of XIX century. Because ХІХ century, especially its second half, was an important transition period for Kazakhstan, which radically changed traditional way of Kazakh society and predetermined further development in consequence of activation of Russian colonial policy and approval of commodity-money relations in Steppe Land.Abai Kunanbayev, besides Arabic and Persian common words and loanwords from Quran in his words of edification, had used a lot of words of Arabic, Persian, Latin, Russian, Nogai, Shaghatai, Polish, Greek, Turkish, which are used in the Kazakh language.

Keywords: Abai Kunanbayev, the Kazakh, Russian languages, literature

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Authors: Sahar Khedr, Dina Sayed, Ayman Hanafy

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Arabic is one of the most ancient and critical languages in the world. It has over than 250 million Arabic native speakers and more than twenty countries having Arabic as one of its official languages. In the past decade, we have witnessed a rapid evolution in smart devices, social network and technology sector which led to the need to provide tools and libraries that properly tackle the Arabic language in different domains. Stemming is one of the most crucial linguistic fundamentals. It is used in many applications especially in information extraction and text mining fields. The motivation behind this work is to enhance the Arabic light stemmer to serve the data mining industry and leverage it in an open source community. The presented implementation works on enhancing the Arabic light stemmer by utilizing and enhancing an algorithm that provides an extension for a new set of rules and patterns accompanied by adjusted procedure. This study has proven a significant enhancement for better search accuracy with an average 10% improvement in comparison with previous works.

Keywords: Arabic data mining, Arabic Information extraction, Arabic Light stemmer, Arabic stemmer.

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Authors: Randa I. M. Elanwar, Mohsen A. Rashwan, Samia A. Mashali

Abstract:

In this paper we present the first Arabic sentence dataset for on-line handwriting recognition written on tablet pc. The dataset is natural, simple and clear. Texts are sampled from daily newspapers. To collect naturally written handwriting, forms are dictated to writers. The current version of our dataset includes 154 paragraphs written by 48 writers. It contains more than 3800 words and more than 19,400 characters. Handwritten texts are mainly written by researchers from different research centers. In order to use this dataset in a recognition system word extraction is needed. In this paper a new word extraction technique based on the Arabic handwriting cursive nature is also presented. The technique is applied to this dataset and good results are obtained. The results can be considered as a bench mark for future research to be compared with.

Keywords: Arabic, Handwriting recognition, on-line dataset.

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Authors: Saher Ali Al-Sabbah, See Ching Mey, Ong Saw Lan

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This article addresses the procedures to validate the Arabic version of Multiple Intelligence Development Assessment Scale (MIDAS). The content validity was examined based on the experts- judgments on the MIDAS-s items in the Arabic version. The content of eleven items in the Arabic version of MIDAS was modified to match the Arabic context. Then a translation from original English version of MIDAS into Arabic language was performed. The reliability of the Arabic MIDAS was calculated based on test and retest method and found to be 0.85 for the overall MIDAS and for the different subscales ranging between 0.78 - 0.87. The examination of construct validity for the overall Arabic MIDAS and its subscales was established by using Winsteps program version 6 based on Rasch model in order to fit the items into the Arabic context. The findings indicated that, the eight subscales in Arabic version of MIDAS scale have a unidimensionality, and the total number of kept items in the overall scale is 108 items.

Keywords: Rasch-Model, validation, multiple intelligence, and MIDAS scale.

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Authors: Ali Ganoun

Abstract:

This paper proposes evaluation of sound parameterization methods in recognizing some spoken Arabic words, namely digits from zero to nine. Each isolated spoken word is represented by a single template based on a specific recognition feature, and the recognition is based on the Euclidean distance from those templates. The performance analysis of recognition is based on four parameterization features: the Burg Spectrum Analysis, the Walsh Spectrum Analysis, the Thomson Multitaper Spectrum Analysis and the Mel Frequency Cepstral Coefficients (MFCC) features. The main aim of this paper was to compare, analyze, and discuss the outcomes of spoken Arabic digits recognition systems based on the selected recognition features. The results acqired confirm that the use of MFCC features is a very promising method in recognizing Spoken Arabic digits.

Keywords: Speech Recognition, Spectrum Analysis, Burg Spectrum, Walsh Spectrum Analysis, Thomson Multitaper Spectrum, MFCC.

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Authors: Mohammed El Amine Abderrahim

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Reformulating the user query is a technique that aims to improve the performance of an Information Retrieval System (IRS) in terms of precision and recall. This paper tries to evaluate the technique of query reformulation guided by an external resource for Arabic texts. To do this, various precision and recall measures were conducted and two corpora with different external resources like Arabic WordNet (AWN) and the Arabic Dictionary (thesaurus) of Meaning (ADM) were used. Examination of the obtained results will allow us to measure the real contribution of this reformulation technique in improving the IRS performance.

Keywords: Arabic NLP, Arabic Information Retrieval, Arabic WordNet, Query Expansion.

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Authors: Salim Ouchtati, Jean Sequeira, Mouldi Bedda

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In the context of the handwriting recognition, we propose an off line system for the recognition of the Arabic handwritten words of the Algerian departments. The study is based mainly on the evaluation of neural network performances, trained with the gradient back propagation algorithm. The used parameters to form the input vector of the neural network are extracted on the binary images of the handwritten word by several methods. The Distribution parameters, the centered moments of the different projections of the different segments, the centered moments of the word image coding according to the directions of Freeman, and the Barr features applied binary image of the word and on its different segments. The classification is achieved by a multi layers perceptron. A detailed experiment is carried and satisfactory recognition results are reported.

Keywords: Handwritten word recognition, neural networks, image processing, pattern recognition, features extraction.

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Authors: A. Dionísio, L. Roseiro, J. Fonseca, P. Nicolau

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Thermography is a non-radiating and contact-free technology which can be used to monitor skin temperature. The efficiency and safety of thermography technology make it a useful tool for detecting and locating thermal changes in skin surface, characterized by increases or decreases in temperature. This work intends to be a contribution for the use of thermography as a methodology for evaluation of skin temperature in the context of orofacial biomechanics. The study aims to identify the oscillations of skin temperature in the left and right hemiface regions of the masseter muscle, during and after thermal stimulus, and estimate the time required to restore the initial temperature after the application of the stimulus. Using a FLIR T430sc camera, a data acquisition protocol was followed with a group of eight volunteers, aged between 22 and 27 years. The tests were performed in a controlled environment with the volunteers in a comfortably static position. The thermal stimulus involves the use of an ice volume with controlled size and contact surface. The skin surface temperature was recorded in two distinct situations, namely without further stimulus and with the additions of a stimulus obtained by a chewing gum. The data obtained were treated using FLIR Research IR Max software. The time required to recover the initial temperature ranged from 20 to 52 minutes when no stimulus was added and varied between 8 and 26 minutes with the chewing gum stimulus. These results show that recovery is faster with the addition of the stimulus and may guide clinicians regarding the pre and post-operative times with ice therapy, in the presence or absence of mechanical stimulus that increases muscle functions (e.g. phonetics or mastication).

Keywords: Thermography, orofacial biomechanics, skin temperature, ice therapy.

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Authors: Seyyed Yasser Hashemi, Khalil Monfaredi

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Automatic transformation of paper documents into electronic documents requires document segmentation at the first stage. However, some parameters restrictions such as variations in character font sizes, different text line spacing, and also not uniform document layout structures altogether have made it difficult to design a general-purpose document layout analysis algorithm for many years. Thus in most previously reported methods it is inevitable to include these parameters. This problem becomes excessively acute and severe, especially in Persian/Arabic documents. Since the Persian/Arabic scripts differ considerably from the English scripts, most of the proposed methods for the English scripts do not render good results for the Persian scripts. In this paper, we present a novel parameter-free method for segmenting the Persian/Arabic document images which also works well for English scripts. This method segments the document image into maximal homogeneous regions and identifies them as texts and non-texts based on a pyramidal image structure. In other words the proposed method is capable of document segmentation without considering the character font sizes, text line spacing, and document layout structures. This algorithm is examined for 150 Arabic/Persian and English documents and document segmentation process are done successfully for 96 percent of documents.

Keywords: Persian/Arabic document, document segmentation, Pyramidal Image Structure, skew detection and correction.

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Authors: Tlili-Guiassa Yamina

Abstract:

Many natural language expressions are ambiguous, and need to draw on other sources of information to be interpreted. Interpretation of the e word تعاون to be considered as a noun or a verb depends on the presence of contextual cues. To interpret words we need to be able to discriminate between different usages. This paper proposes a hybrid of based- rules and a machine learning method for tagging Arabic words. The particularity of Arabic word that may be composed of stem, plus affixes and clitics, a small number of rules dominate the performance (affixes include inflexional markers for tense, gender and number/ clitics include some prepositions, conjunctions and others). Tagging is closely related to the notion of word class used in syntax. This method is based firstly on rules (that considered the post-position, ending of a word, and patterns), and then the anomaly are corrected by adopting a memory-based learning method (MBL). The memory_based learning is an efficient method to integrate various sources of information, and handling exceptional data in natural language processing tasks. Secondly checking the exceptional cases of rules and more information is made available to the learner for treating those exceptional cases. To evaluate the proposed method a number of experiments has been run, and in order, to improve the importance of the various information in learning.

Keywords: Arabic language, Based-rules, exceptions, Memorybased learning, Tagging.

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Authors: Gehad S. Kaseb, Mona F. Ahmed

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Arabic Sentiment Analysis (SA) is one of the most common research fields with many open areas. This paper proposes different pre-processing steps and a modified methodology to improve the accuracy using normal Support Vector Machine (SVM) classification. The paper works on two datasets, Arabic Sentiment Tweets Dataset (ASTD) and Extended Arabic Tweets Sentiment Dataset (Extended-ATSD), which are publicly available for academic use. The results show that the classification accuracy approaches 86%.

Keywords: Arabic, hybrid classification, sentiment analysis, tweets.

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Authors: Randa I. Elanwar, Mohsen A. Rashwan, Samia A. Mashali

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The last two decades witnessed some advances in the development of an Arabic character recognition (CR) system. Arabic CR faces technical problems not encountered in any other language that make Arabic CR systems achieve relatively low accuracy and retards establishing them as market products. We propose the basic stages towards a system that attacks the problem of recognizing online Arabic cursive handwriting. Rule-based methods are used to perform simultaneous segmentation and recognition of word portions in an unconstrained cursively handwritten document using dynamic programming. The output of these stages is in the form of a ranked list of the possible decisions. A new technique for text line separation is also used.

Keywords: Arabic handwriting, character recognition, cursive handwriting, on-line recognition.

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Authors: Nadia Hmad, Tony Allen

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This paper presents an ESN-based Arabic phoneme recognition system trained with supervised, forced and combined supervised/forced supervised learning algorithms. Mel-Frequency Cepstrum Coefficients (MFCCs) and Linear Predictive Code (LPC) techniques are used and compared as the input feature extraction technique. The system is evaluated using 6 speakers from the King Abdulaziz Arabic Phonetics Database (KAPD) for Saudi Arabia dialectic and 34 speakers from the Center for Spoken Language Understanding (CSLU2002) database of speakers with different dialectics from 12 Arabic countries. Results for the KAPD and CSLU2002 Arabic databases show phoneme recognition performances of 72.31% and 38.20% respectively.

Keywords: Arabic phonemes recognition, echo state networks (ESNs), neural networks (NNs), supervised learning.

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Authors: Khalid A. Darabkh, Ala F. Khalifeh, Baraa A. Bathech, Saed W. Sabah

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Despite the fact that Arabic language is currently one of the most common languages worldwide, there has been only a little research on Arabic speech recognition relative to other languages such as English and Japanese. Generally, digital speech processing and voice recognition algorithms are of special importance for designing efficient, accurate, as well as fast automatic speech recognition systems. However, the speech recognition process carried out in this paper is divided into three stages as follows: firstly, the signal is preprocessed to reduce noise effects. After that, the signal is digitized and hearingized. Consequently, the voice activity regions are segmented using voice activity detection (VAD) algorithm. Secondly, features are extracted from the speech signal using Mel-frequency cepstral coefficients (MFCC) algorithm. Moreover, delta and acceleration (delta-delta) coefficients have been added for the reason of improving the recognition accuracy. Finally, each test word-s features are compared to the training database using dynamic time warping (DTW) algorithm. Utilizing the best set up made for all affected parameters to the aforementioned techniques, the proposed system achieved a recognition rate of about 98.5% which outperformed other HMM and ANN-based approaches available in the literature.

Keywords: Arabic speech recognition, MFCC, DTW, VAD.

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Authors: Abdulfatah A Raji

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This paper started with the definitions of literature, Arabic literature, transformation and went further to highlight the components of educational transformation. The general history of Arabic literature was discussed with focus on how it undergoes some transformations from pre-Islamic period through Quranic era, Abbasid literature to renaissance period in which the modernization of Arabic literature started in Egypt. It also traces the spread of Arabic literature in Nigeria from the pre-colonial era during the Kanuri rulers to Jihad of Usman Dan Fodio and the development of literature which manifested to the Teacher’s Colleges and Bayero University in Northern Nigeria. Also, the establishment of primary and post-primary schools by Muslim organizations in many cities and towns of the Western part of Nigeria. Literary criticism was also discussed in line with Arabic literature. Poetry work of eminent poets were cited to show its importance in line with educational transformation in Nigerian literature and lessons from the cited Arabic poetry works were also highlighted to include: motivation to behave well and to tolerate others, better spirits of interaction, love and co-existence among different sexes, religion etc. All these can help in developing a better educational transformation in Nigeria which can in turn help in how to conduct researches for national development. The paper recommended compulsory Arabic literature at all levels of the nations’ educational system as well as publication of Arabic books and journals to encourage peace in this era of conflicts and further transform Nigeria’s educational system for better.

Keywords: Arabic, literature, peace, development, Nigeria

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Authors: Adel Assiri, Ahmed Emam, Hmood Al-Dossari

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Sentiment analysis (SA) has received growing attention in Arabic language research. However, few studies have yet to directly apply SA to Arabic due to lack of a publicly available dataset for this language. This paper partially bridges this gap due to its focus on one of the Arabic dialects which is the Saudi dialect. This paper presents annotated data set of 4700 for Saudi dialect sentiment analysis with (K= 0.807). Our next work is to extend this corpus and creation a large-scale lexicon for Saudi dialect from the corpus.

Keywords: Arabic, Sentiment Analysis, Twitter, annotation.

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Authors: Mohammad AL Amro

Abstract:

This study will provide a brief description of the stress in Najdi Arabic dialect as well as Modern Standard Arabic. Beyond the analysis of stress patterns, this paper will also attempt to deal with two important phenomena that affect stress, namely epenthesis/insertion, vowel shortening, and consonant (the glottal stop) deletion.

Keywords: Epenthesis, Najd, stress, vowel shortening.

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Authors: R. Rahmoun-Mrabet

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It is acknowledged that our style of speaking changes according to a wide range of variables such as gender, setting, the age of both the addresser and the addressee, the conversation topic, and the aim of the interaction. These differences in style are noticeable in monolingual and multilingual speech communities. Yet, they are more observable in speech communities where two or more codes coexist. The linguistic situation in Algeria reflects a state of bilingualism because of the coexistence of Arabic and French. Nevertheless, like all Arab countries, it is characterized by diglossia i.e. the concomitance of Modern Standard Arabic (MSA) and Algerian Arabic (AA), the former standing for the ‘high variety’ and the latter for the ‘low variety’. The two varieties are derived from the same source but are used to fulfil distinct functions that is, MSA is used in the domains of religion, literature, education and formal settings. AA, on the other hand, is used in informal settings, in everyday speech. French has strongly affected the Algerian language and culture because of the historical background of Algeria, thus, what can easily be noticed in Algeria is that everyday speech is characterized by code-switching from dialectal Arabic and French or by the use of borrowings. Tamazight is also very present in many regions of Algeria and is the mother tongue of many Algerians. Yet, it is not used in the west of Algeria, where the study has been conducted. The present work, which was directed in the speech community of Tlemcen-Algeria, aims at depicting some of the outcomes of the contact of Arabic with French such as code-switching, borrowing and interference. The question that has been asked is whether Algerians are aware of their use of borrowings or not. Three steps are followed in this research; the first one is to depict the sociolinguistic situation in Algeria and to describe the linguistic characteristics of the dialect of Tlemcen, which are specific to this city. The second one is concerned with data collection. Data have been collected from 57 informants who were given questionnaires and who have then been classified according to their age, gender and level of education. Information has also been collected through observation, and note taking. The third step is devoted to analysis. The results obtained reveal that most Algerians are aware of their use of borrowings. The present work clarifies how words are borrowed from French, and then adapted to Arabic. It also illustrates the way in which singular words inflect into plural. The results expose the main characteristics of borrowing as opposed to code-switching. The study also clarifies how interference occurs at the level of nouns, verbs and adjectives.

Keywords: Bilingualism, borrowing, code-switching, interference, language contact.

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Authors: Smail Hadj Mahammed

Abstract:

Translation is not merely a process of conveying the meaning from one particular language into another to overcome language barriers and ensure a good understanding; it is also a work of civilization and progress. Without the translation of Greek, Indian and Persian works, Arabic and Islamic Civilization would not have taken off, and without the translations of Arabic works into Latin, and then into European languages, the scientific and technological revolution of the modern world would not have taken place. In this context, the present paper seeks to investigate how the translation movement contributed to the Arabic and Islamic Civilizations during the Golden Age. The paper consists of three major parts: the first part provides a brief historical overview of the translation movement during the golden age, which witnessed two important eras: the Umayyad and Abbasid eras. The second part shows the main reasons why translation was a prominent cultural activity during the Golden Age and why it gained great interest from the Arabs. The last part highlights the constructive contribution of translation to the Arabic and Islamic Civilization during the period (661–1258). The results demonstrate that Arabic translation movement during the Golden Age had significantly assisted in enriching the Arabic and Islamic civilizations considering the major and important scientific works of old Greek, Indian and Persian civilizations which had been absorbed.

Keywords: Arabic and Islamic civilization, contribution, golden age, translation.

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Authors: Salima Behdenna, Fatiha Barigou, Ghalem Belalem

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Due to the quick increase in the volume of Arabic opinions posted on various social media, Arabic sentiment analysis has become one of the most important areas of research. Compared to English, there is very little works on Arabic sentiment analysis, in particular aspect-based sentiment analysis (ABSA). In ABSA, aspect extraction is the most important task. In this paper, we propose a semantic ABSA approach for standard Arabic reviews to extract explicit aspect terms and identify the polarity of the extracted aspects. The proposed approach was evaluated using HAAD datasets. Experiments showed that the proposed approach achieved a good level of performance compared with baseline results. The F-measure was improved by 19% for the aspect term extraction tasks and 55% aspect term polarity task.

Keywords: Sentiment analysis, opinion mining, Arabic, aspect level, opinion, polarity.

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Authors: Adnan Abdul-Aziz Gutub, Manal Mohammad Fattani

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This paper presents a new steganography approach suitable for Arabic texts. It can be classified under steganography feature coding methods. The approach hides secret information bits within the letters benefiting from their inherited points. To note the specific letters holding secret bits, the scheme considers the two features, the existence of the points in the letters and the redundant Arabic extension character. We use the pointed letters with extension to hold the secret bit 'one' and the un-pointed letters with extension to hold 'zero'. This steganography technique is found attractive to other languages having similar texts to Arabic such as Persian and Urdu.

Keywords: Arabic text, Cryptography, Feature coding, Information security, Text steganography, Text watermarking.

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