This paper presents a method for converting Persian text written in a romanized writing system (Dabire) to the tra- ditional Arabic-based orthography. Related work includes (Johanson, 2007) which introduces a method for convert- ing names written in the PA-Script to Latin. (Kashani et al., 2007) uses letter-based alignment in automatic transliter- ation of proper nouns in Arabic to English, and (Beesley, 2007) applies morphological analysis to transcription to Arabic. However, we are not aware of any earlier work on automatic transcription from romanized to arabized Per- sian.
shows these vowel sets and other equivalent letters. These simple matching rules make rhyme detection in Arabic a much simpler task compared to English where different sets of letter combinations can sig- nal the same rhyme (Tizhoosh & Dara 2006). On the other hand, the fact that, in modern Arabicwriting, short vowels are ignored adds more chal- lenges for the rhyme identification process. How- ever, in poetry typesetting, typists tend not to omit short vowels especially for poems written in stan- dard Arabic.
In considering the pervasiveness of coordination in Modern Standard Arabic, this article has attempted to extend the domain of investigation beyond previous studies. By bringing together the findings of such studies, the article has attempted to site them within a wider conceptual framework, with the aim of gaining more integrated insights into why Arabic and English differ in the use of coordination. Thus, while previous studies concentrated on the fact, as a general writing feature, of the greater use of coordination in Arabic than English, particularly to link clauses or sentences, this article has argued that not only is coordination a general feature of Arabicwriting, but that various linguistic, textual and ‘rhetorical semantic’ norms work individually – and sometimes in combination – to further entrench coordination as a feature of Modern Standard Arabic. Coordination is thus more ‘hard - wired’ in Modern Standard Arabic than a simple statistical analysis of its relative predominance would suggest. This perspective suggests a new approach to Arabic coordination. This would consider in greater detail (e.g. through larger and more coherent corpora) than in the current study the relationship between the general fact of the prominence of coordination in Arabic and the way this interacts with the linguistic, textual and ‘rhetorical semantic’ norms identified in this article and with other similar norms perhaps still awaiting identification and analysis.
Classification technique involves identifying which of set of important features a new observation belongs, on the basis of training set of Arabicwriting containing observations. Here, we use Decision Tree (DT) as the classifier. DT classifier calculates the distance between two corresponding points. This technique is used to measure the similarity between the important features of the test image with the important feature gallery obtained during the training process. Classification trees and regression trees  predict responses to data. To predict a response, follow the decisions in the tree from the root (beginning) node down to a leaf node. The leaf node contains the response. Classification trees give responses that are nominal, such as 'true' or 'false'. Regression trees give numeric responses. Each step in a prediction involves checking the value of one predictor (variable). The classification tree and the regression tree methods perform the following steps to create decision trees: 1. Start with all input data, and examine all possible binary splits on every predictor. 2. Select a split with best optimization criterion. 3. If the split leads to a child node having too few observations (less than the minimum leaf parameter), select a split with the best optimization criterion subject to the minimum leaf constraint. Impose the split. Repeat recursively for the two child nodes.
Arabic as an L1 may also influence more global concerns, such as organization and content development, and the attitude toward language learning. For instance, according to Murad and Khalil (2015), the major challenges faced by Arab speakers learning English were in content and organization in addition vocabulary as well as language usage. Dewaele and Nakano (2012) suggest that the first language has a way of influencing people‘s perceptions, which may result in differences in what is privileged as ―good writing,‖ and may also affect their attitude towards learning a second language. For example, many people consider their first languages to be real and natural whereas the second language is often presumed as fake (Dawaele & Nakano, 2012). This perception, however, acts as a challenge as it sometimes discourages them from learning the second language effectively. For example, a challenge for L1 Arabic students is to express their ideas clearly in the common English genre of the essay (Bacha, 2017). Bacha‘s (2017) analysis of first year university L1 Arabic students‘ essays shows conflicting L1 rhetorical patterns in the written essays that led to a lack of clarity in the essays. However, questionnaire findings revealed that students do not view any significant interference from L1 nor any significant problems in writing the academic essays that are contradictory to the essay scores and content analysis results. A lack of understanding of the different expectations of English writing compared to Arabicwriting may therefore limit EFL learners‘ literacy. In addition, researchers have also suggested that Arabic writers may have distinctive English writing strategies, such as an emphasis on planning in one‘s head rather than on paper (see Section 3.7.2). Therefore, the cognitive process of writing for Kuwaiti learners of English is not only a reformulation of knowledge, but also a structural task in reformatting their writing (Farthing, 2015). The next section begins the discussion of writing strategies in L2 to lay foundation for the discussion of Kuwaiti EFL students‘ writing strategies.
Thinning is a process to reduce the foreground regions in the binary image of the remains to the skeleton that keeps largely on the extent of the contact in the original region while throwing more than the original foreground. Commonly used in pattern recognition, digital image processing and image analysis. The thinning process is applying to enhanced images words. An effectively skeleton algorithm has been proven in a wide range of applications for image processing including the OCR. Skeleton algorithm will find a single pixel thick representation showing centerlines of the text. Generally, skeletonization algorithm to be effective, it should ideally data compression and retaining the important features of this pattern. For the case of handwritten Arabic it is hard to find a robust and useful skeleton algorithm that retains the significant feature of the pattern due to the variety of handwritten Arabicwriting styles. This paper has been used the thinning algorithm that is based on the Zhang-Suen’s thinning algorithm . The Zhang-Suen’s thinning algorithm for extracting the skeleton of a picture consists of removing all the contour points of the picture except those points that belong to the skeleton. In order to preserve the connectivity of the skeleton, it divides iteration into two sub iterations. In the first sub iteration, the contour point P 1 is
Arabic language is the official language of 24 countries and it is spoken by almost more than 422 million people. The Arabic alphabet contains 28 letters, words are written in horizontal lines from right to left. Moreover, Arabic books and documents are written using different font's types and styles. The recent researches on Arabic language related to documents digitization has been focusing on word and handwriting recognition , and neglecting the layout analysis of Arabic documents relaying on methods proposed for documents of other languages such as Latin and English. Correct document layout analysis is a key step of the conversion of captured or scanned documents into electronic formats, optical character recognition (OCR), reformatting of documents for on-screen display. Moreover, the performance of any further layout processing is totally depends on the text and non-text segmentation.
8. Name authority work presents a problem when specifically Judeo-Arabic names are involved—e.g., the forename /Mqyqṣ/. A group such as the Association of Jewish libraries may choose to keep an online list of found romanizations and code such headings (romanized as seems reasonable) “provisional” until they can be added to the list of authorized forms. Robert Attal’s ”ha-Sifrut ha-ʻArvit- ha-Yehudit be-Tunisyah : meʼah shenot yetsirah (1861-1961) : tsiyunim
These figures are of strong indication of a cultural and linguistic crisis of Arabic. This is due to the fact that the two synynoms Alghaith and Almatar are not absolute synonyms. In fact, it is belived by many ancient and contemporary Arabic linguists that there are no absolute synonyms in Arabic, and that there exists, definitely, a differnce in meaning between every pair of synonyms. This thoery applies to the two synonyms Alghaith and Almatar; the word Alghaith refers to the rain that falls when people and crops are of great need and thurst, and also to the rain that does not cause any damage to people, cattle, crops, property, etc. On the other hand, the word Almatar can be used to describe the rain that causes damages or the rain that does not . A look at the figures in Table 2 shows a drastic decrease in the usage of the word Alghaith in modern literature. The use of that word decreases even further, as expected, in common daily language use as in newspapers articles where it reaches a frequency rate of (0.27/100,000) 6 ; it is barely used.
Objective: linguistic validation in Moroccan Arabic dialect of overactive bladder questionnaires OAB-q, developed and validated initially in English. Materials and Methods: Questionnaire OAB-q Moroccan Arabic dialect ver- sion was obtained after a double translation (English-Arabic), a back transla- tion (Arabic-English), a journal of translations by three experts, comprehen- sion tests and cultural adaptation on a sample of 10 patients with overactive bladder syndrome. Results: The OAB-q in two parts. The first eight items had assessed the discomfort associated with symptoms of overactive bladder (uri- nary frequency day and night, urgency and urge incontinence). The second included 25 items and measured the impact on quality of life (coping beha- vior, embarrassment, sleep, social interactions). The conceptual and cultural adaptation was performed on a sample of 10 patients (5 with multiple sclero- sis, 5 spinal cord injuries), the average age is 42, 4 +/− 7.6, the sex ratio is 1. Discussion and Conclusion: OAB-q has been validated in men and women with symptoms of overactive bladder with or without incontinence (a neuro- logical or not). Internal consistency and discriminative construct validity were demonstrated. It has been well validated in patients with multiple sclerosis and spinal cord injury. The linguistic validation Moroccan Arabic dialect is the ini- tial step pending a psychometric validation with larger number of patients.
Most advanced mobile applications re- quire server-based and communication. This often causes additional energy con- sumption on the already energy-limited mobile devices. In this work, we provide to address these limitations on the mobile for Opinion Mining in Arabic. Instead of relying on compute-intensive NLP pro- cessing, the method uses an Arabic lexi- cal resource stored on the device. Text is stemmed, and the words are then matched to our own developed ArSenL. ArSenL is the first publicly available large scale Standard Arabic sentiment lexicon (ArSenL) developed using a combination of English SentiWordnet (ESWN), Arabic WordNet, and the Ara- bic Morphological Analyzer (AraMorph). The scores from the matched stems are then processed through a classifier for determining the polarity. The method was tested on a published set of Arabic tweets, and an average accuracy of 67% was achieved. The developed mobile ap- plication is also made publicly available. The application takes as input a topic of interest and retrieves the latest Arabic tweets related to this topic. It then dis- plays the tweets superimposed with col- ors representing sentiment labels as posi- tive, negative or neutral. The application also provides visual summaries of searched topics and a history showing how the sentiments for a certain topic have been evolving.
Such understanding makes our interaction with the Arab world at once more meaningful and eff ective, or, if you want, less disruptive and ad hoc. It is based on the weight carried by places, buildings, behaviour, memories and symbols and the constantly moving historical threads that connect them. These multitude of messages and layers in cultural expression and interac- tion, of which the spoken and written words are in fact only the easiest to be apprehended, can only be fully understood in the round, by data and insights from all angles of understanding. In Leiden we are able not only to draw upon a huge reservoir of such experts working in multiple languages and disciplines – already Erpenius and Scaliger thought Arabic should be studied together with Turkish and Persian, an ideal that continues to be upheld by this university – but our informants also extend into the past as we build on the knowledge and experience of generations of predecessors. Again, this depth of insight is beyond a single individual, however much experience and erudition he or she can boast. Moreover, it cannot be learned from books alone, but requires an active, living body of researchers, scholars, teachers and students, and a constantly evolving, updated and upgraded knowledge base. Without such a continuously renewing critical mass, the chain will be broken, a rupture that cannot lightly be compensated for.
countries in the Middle East and beyond. Sudanese Arabic as reported by Agency 2 is assumed to be the Sudanese variety of colloquial spoken Arabic used extensively in Sudan, although it may also include the Arabic-based Creole, Juba Arabic, which is also quite widely spoken as a lingua franca in the South. Some care needs to be exercised in interpreting this data on language requests. Qualified interpreters are not currently available for a number of the emerging African languages. If/once a client or agency becomes aware that the preferred language is not likely to be available they may then not request that language, rather opting for a second language that the client may have some knowledge of and for which they know that interpreting is available, such as an official national language (eg. Somali), or a local lingua franca (eg. Swahili, Sudanese Spoken Arabic or Juba Arabic).
spoken in North Africa including Morocco, Libya, Tunisia, Algeria, Mauritania and Algeria, and they are subdivided into pre-Hilāli sedentary dialects and Bedouin dialects. The Western dialect group is mainly characterised by paradigmatically levelled inflection in the first person imperfect, e.g. niktib ‘we write’, niktibu ‘we write it’, a loss of inherited short vowels in medial positions and non-phonemic vowel quantity (Palva 2006). The Eastern dialect group Mašriqī is spoken in the Middle Eastern 10 countries and it is characterised by retention of the first person singular and plural inflection in the imperfect, as in: aktib ‘I write’, niktib ‘we write’, and maintenance of distinction between three short vowels. Sociologically, Arabic dialects are classified into sedentary ħaḍarī and Bedouin badawī (Palva 2006; Rosenhouse 2006). This division is based on the history of settlement and the language shift that has been taking place and applies to dialects in the entire Arabic-speaking world with some degree of variations. Sedentary dialects are sub-divided into urban madanī and rural qarawī. Based on their way of living, Bedouin dialects are further classified into nomadic and semi-nomadic groups (Rosenhouse 2006). Bedouin dialects are also classified into those which have phonetically conditioned affrication of /g/ and /k/ (many Peninsular dialects) and those which do not have affricated allophones (Northwest Arabian dialects, Egyptian and North African dialects) (Palva 2006: 606). Bedouin dialects are said to be more conservative than sedentary dialects since they have preserved more morpho-phonemic categories than the sedentary dialects (Palva 2006: 606). Palva (2006: 606) presents a number of linguistic features that characterise Bedouin and sedentary Arabic dialects. In the table below, the letter ‘A’ indicates a feature that pertains to all the dialects of the group and the letter ‘P’ indicates a feature that characterises a partial part of the group.
Applying (burrows-Delta and SABA) algorithms usually depends on the frequency of the word as the best attribute that can be used to get the best prediction in the style of the writer, greater number of words frequencies will increase the prediction percentage of author's style and vice-versa, the challenge in Arabic language that the feminine and masculine will change the shape of adjectives and verbs that which reduces the redundancy, for example the words “ ليمج” or “ لليمج” means in English “beautiful” which represent two frequencies in English while it represent one frequency in Arabic, as well as the word “play” means in Arabic “بعل ” for male or “تبعل ” for female.
Arabic is often written using Latin characters in transliterated form, which is often referred to as Ara- bizi, Arabish, Franco-Arab, and other names. Ara- bizi uses numerals to represent Arabic letters for which there is no phonetic equivalent in English or to account for the fact that Arabic has more letters than English. For example, “2” and “3” represent the letters @ (that sounds like “a” as in apple) and ¨ (that is a guttural “aa”) respectively. Arabizi is par- ticularly popular in Arabic social media. Arabizi has grown out of a need to write Arabic on systems that do not support Arabic script natively. For example, Internet Explorer 5.0, which was released in March 1999, was the first version of the browser to sup-
Methodologies proposed by El-Beltagy, Samhaa R., and Ahmad Ali (2010) in ; the study reviewed the problems and challenges for sentiment Analysis in social media. The researchers investigate the possibility of determining the semantic orientation of Arabic Egyptian tweets and comments by using two data sets. Twitter dataset contained 500 tweets. 310 tweets were classified as negative, 155 as positive, and 35 as Neutral. Dostour dataset consisted of 100 comments randomly collected. 38 comments were negative, 40 classified as positive and 22 as neutral. The outcome of study was an Egyptian dialect sentiment lexicon.
Van der Hulst & Hellmuth (2010) point out that the minimal stress pairs which crucially distinguish one dialect from another are relatively infrequent, occurring only in words of certain prosodic shapes. This in turn means that, for the bulk of words, more than one set of parameters could account for the data, allowing for variation in which parameter settings language learners infer from them. These apparently minor surface differences between dialects have on occasion been instrumental in the development of metrical theory. For example, Watson (2011) describes how the particular patterns observed in morphologically complex words in Bedouin Hijazi Arabic (Al-Mozainy et al. 1985) led to the proposal of the bracketed metrical grid (Halle & Vergnaud 1987, Hayes 1995), a representation which encodes prosodic constituency at different levels. In a similar way, Arabic dialects show variation in the sensitivity of stress assignment to morphological structure (Brame 1973, 1974), and these facts were instrumental in the development of theories such as Lexical Phonology (Kiparsky 1982) and Stratal OT (Kiparsky 2000). Equally, the interaction of stress assignment with segmental processes is well-known in Arabic for giving rise to cases of opacity, in which the triggering context for a phonological process is not apparent in the surface form of the word. Such cases present a particular challenge to non-derivational theories of phonology, such as classic OT, and a sizeable body of literature has sought ways to analyse such cases of opacity (McCarthy 2003, Elfner 2009). Finally, the literature includes one or two interesting cases of dialects in which citation form word stress assignment patterns are subject to variation in connected speech. In Sanaani Arabic for
Burch’s (2014) paper that described this dataset. The authors collected words for all dialects from readers' comments on the online websites of three Arabic newspapers: Al-Ghad from Jordan to cover the Levantine dialect, Al-Riyadh from Saudi Arabia to cover the Gulf dialect, and Al-Youm Al-Sabe from Egypt to cover the Egyptian dialect (ibid). In addition, we used some seed words from Almeman and Lee (2013) paper . The researchers collected 1,500 words and phrases by exploring the web and extracting dialects’ words and phrases, which must be found in one dialect of the four main dialects which are GLF, LEV, EGY, and MAG. We did not find a corpus for the Iraqi dialect, but we extracted some IRQ seed words from . All dialect seed words we have chosen seem to be popular and frequently used in this dialect and usually we hear them from native speakers for each dialect or on TV programs or movies.
Most of the research on Arabic is focused on Mod- ern Standard Arabic. Dialectal varieties have not received much attention due to the lack of dialectal tools and annotated texts (Duh and Kirchoff, 2005). In this paper, we present a rule-based me- thod to generate Colloquial Egyptian Arabic (CEA) from Modern Standard Arabic (MSA), relying on segment-based part-of-speech tags. The transfor- mation process relies on the observation that di- alectal varieties of Arabic differ mainly in the use of affixes and function words while the word stem mostly remains unchanged. For example, given the Buckwalter-encoded MSA sentence “AlAxwAn Almslmwn lm yfwzwA fy AlAntxbAt” the rules pro- duce “AlAxwAn Almslmyn mfAzw$ f AlAntxAbAt” (تاباختولاا ف شوزافم هيملسملا ناىخلاا, The Muslim Bro- therhood did not win the elections). The availabili- ty of segment-based part-of-speech tags is essential since many of the affixes in MSA are ambiguous. For example, lm could be either a negative particle or a question work, and the word AlAxwAn could be either made of two segments (Al+<xwAn, the