The Routledge course in Arabic business translation: Arabic-English-Arabic
PERSPECTIVES-STUDIES IN TRANSLATION THEORY AND PRACTICE(2023)
摘要
The use of tools and apps to understand more about a language has become popular in recent years. This technology assists the learner in gaining more knowledge about a specific language's vocabulary, collocations, grammar, etc. An example is a concordancer, which is a kind of program that can offer valuable knowledge in multiple contexts regarding the frequency of terms or word. The production of such a tool for Arabic has been limited for several years due to the complexities of the language. The purpose of this paper is therefore to create an automatic Arabic concordancer (auto-CON) with a simple GUI. The proposed method extracts information from a corpus and then provide the needed information depending on a user query. The main aim of the proposed concordance is to provide users with more information on the search word, including the concordance of theword entered, the origin of theword, the domain of each concordance, and the terms extracted from the same root word. The auto-CON tool relies on the creation of two dictionaries: the first dictionary contains all the occurrences and concordances of the word in the corpus, while the second dictionary provides the roots of the words and the words derived from those roots. Therefore, the auto-CON tool is designed to be an educational tool that could support learners of Arabic and Arabic societies. In addition, it can serve as a convenient method for people of different ages to gain more comprehensive knowledge about Arabic words and their concordances. The contribution of this tool is to develop the domain of Arabic NLP. This proposed approach was examined by user testing, in which two Arabic speakers and Arabic learners (international students) were asked to test the approach and provide feedback. The result of the user testing presented the effectiveness of the proposed method.
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关键词
Arabic dialect,Colloquial Egyptian Arabic,Modern Standard Arabic,colloquial Arabic,MSA data,unseen CEA text,English machine translation,NLP task,POS tagging,dialectal variety,standard Arabic
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