A Lexical Distance Study of Arabic Dialects

Kwaik, Kathrein Abu; Saad, Motaz; Chatzikyriakidis, Stergios; Dobnika, Simon

doi:10.1016/j.procs.2018.10.456

Cited by 46 publications

(11 citation statements)

References 16 publications

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“…People from Syria speak Levantine Arabic. This form differs from MSA in vocabulary, morphology, phonology, and even syntax (Kwaik et al, 2018;Saiegh-Haddad & Schiff, 2016). Upon entering school these children often have experiences learning MSA that are similar to learning an additional language.…”

Section: Overview Of the Arabic Languagementioning

confidence: 99%

Word reading in English and Arabic in children who are Syrian refugees

Gottardo

Amin

et al. 2020

Applied Psycholinguistics

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Word reading is a fundamental skill in reading and one of the building blocks of reading comprehension. Theories have posited that for second language (L2) learners, word reading skills are related if the children have sufficient experience in the L2 and are literate in the first language (L1). The L1 and L2 reading, phonological awareness skills, and morphological awareness skills of Syrian refugee children who speak Arabic and English were measured. These children were recent immigrants with limited L2 skills and varying levels of L1 education that was often not commensurate with their ages. Within- and across-language skills were examined in 96 children, ages 6 to 13 years. Results showed that phonological awareness and morphological awareness were strong within-language variables related to reading. Additionally, Arabic phonological awareness and morphological processing were strongly related to English word reading. Commonality analyses for variables within constructs (e.g., phonological awareness, morphological awareness) but across languages (Arabic and English) in relation to English word reading showed that in addition to unique variance contributed by the variables, there was a high degree of overlapping variance.

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Section: Overview Of the Arabic Languagementioning

confidence: 99%

Word reading in English and Arabic in children who are Syrian refugees

Gottardo

Amin

et al. 2020

Applied Psycholinguistics

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“…Limited previous research has focused on studying the differences between Arabic dialects. In one study, the authors considered several corpora that consisted of countrylevel dialects and compared their commonalities [36]. The authors studied the different dialects' similarity to Modern Standard Arabic and found that "Levantine dialects are in general the closest to MSA, while the North African dialects are the farthest," despite the fact that none of the corpora used in their research included data from the Gulf region.…”

Section: Studying Similarities Between Arabic Dialectsmentioning

confidence: 99%

“…The authors compared the similarities between texts collected from four countries. In the previously-described paper by Kwaik et al [36], the authors also compared dialects collected from the four countries in their corpus. They concluded that there is "great overlap between the dialects and dispersion of lexical items between categories," while also acknowledging that there was "a little similarity between the two dialects on the lexical level" when classifying only Jordanian and Lebanese texts.…”

Section: Studying Similarities Between Arabic Dialectsmentioning

confidence: 99%

Similarities between Arabic dialects: Investigating geographical proximity

Alsudais

Alotaibi²,

Alomary³

2022

Information Processing & Management

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“…2016; Abu Kwaik et al . 2018). In addition, the reader commentary from online Arabic newspapers were used to build corpora for Arabic dialects by Zaidan and Callison-Burch (2011, 2014), and Cotterell and Callison-Burch (2014).…”

Section: Resources For Adimentioning

confidence: 99%

“…2018; Mubarak 2018; Zaghouani and Charfi 2018; Abu Kwaik et al . 2018; Abdul-Mageed, Alhuzali, and Elaraby 2018; Bouamor, Hassan, and Habash 2019). User comments on YouTube videos have also been utilised to build dialectal corpora for a number of Arabic dialects (Salama et al .…”

Section: Resources For Adimentioning

confidence: 99%

Creation of annotated country-level dialectal Arabic resources: An unsupervised approach

Althobaiti

2021

Nat. Lang. Eng.

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The wide usage of multiple spoken Arabic dialects on social networking sites stimulates increasing interest in Natural Language Processing (NLP) for dialectal Arabic (DA). Arabic dialects represent true linguistic diversity and differ from modern standard Arabic (MSA). In fact, the complexity and variety of these dialects make it insufficient to build one NLP system that is suitable for all of them. In comparison with MSA, the available datasets for various dialects are generally limited in terms of size, genre and scope. In this article, we present a novel approach that automatically develops an annotated country-level dialectal Arabic corpus and builds lists of words that encompass 15 Arabic dialects. The algorithm uses an iterative procedure consisting of two main components: automatic creation of lists for dialectal words and automatic creation of annotated Arabic dialect identification corpus. To our knowledge, our study is the first of its kind to examine and analyse the poor performance of the MSA part-of-speech tagger on dialectal Arabic contents and to exploit that in order to extract the dialectal words. The pointwise mutual information association measure and the geographical frequency of word occurrence online are used to classify dialectal words. The annotated dialectal Arabic corpus (Twt15DA), built using our algorithm, is collected from Twitter and consists of 311,785 tweets containing 3,858,459 words in total. We randomly selected a sample of 75 tweets per country, 1125 tweets in total, and conducted a manual dialect identification task by native speakers. The results show an average inter-annotator agreement score equal to 64%, which reflects satisfactory agreement considering the overlapping features of the 15 Arabic dialects.

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A Lexical Distance Study of Arabic Dialects

Cited by 46 publications

References 16 publications

Word reading in English and Arabic in children who are Syrian refugees

Word reading in English and Arabic in children who are Syrian refugees

Similarities between Arabic dialects: Investigating geographical proximity

Creation of annotated country-level dialectal Arabic resources: An unsupervised approach

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