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The objective of this work is to perform a spell check tool that analyzes the text entered in search for possible misspellings. This tool will suggest possible corrections for each misspelled word in the text. This work will require the presence of a reference dictionary of words in the arabic language. These objective Were Accomplished with resources, effective methods, and approaches. First experimental results on real data are encouraging and provide evidence of the validity of the design choices. They also help to highlight the difficulty of the task, and suggest possible developments.

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our work fits into the project entitled "TELA": an environment for learning the Arabic language computer-assisted, which covers many issues related to the use of words in Arabic. This environment contains several subsystems whose purpose is to provide an important educational function by allowing the learner to discover information beyond the scope of the phrase of the year. In these subsystems there are semantic analyzers which have several features and multifunctions (Arabic-English machine translation, Arabic-English machine translation, derivation, and conjugation, etc.). Therefore, in this article we focused upon the design of machine translation systems on the pair of Arabic / English based on statistical models.