Arabic diacritics are often missed in Arabic scripts. This feature is a handicap for new learner to read َArabic, text to speech conversion systems, reading and semantic analysis of Arabic texts.The automatic diacritization systems are the best solution to handle this issue. But such automation needs resources as diactritized texts to train and evaluate such systems.In this paper, we describe our corpus of Arabic diacritized texts. This corpus is called Tashkeela. It can be used as a linguistic resource tool for natural language processing such as automatic diacritics systems, dis-ambiguity mechanism, features and data extraction.The corpus is freely available, it contains 75 million of fully vocalized words mainly 97 books from classical and modern Arabic language.The corpus is collected from manually vocalized texts using web crawling process.

Automatic correction of misspelled words means offering a single proposal to correct a mistake, for example, switching two letters, omitting letter or a key press. In Arabic, there are some typical common errors based on letter errors, such as confusing in the form of Hamza ‫,ھﻤﺰة‬ confusion between Daad ‫ﺿﺎد‬ and Za ‫,ﻇﺎء‬ and the omission dots with Yeh ‫ﯾﺎء‬ and Teh ‫ﺗﺎء‬. So we propose in this paper a system description of a mechanism for automatic correction of common errors in Arabic based on rules, by using two methods, a list of words and regular expressions.

Text to speech (TTS) is a crucial tool needed in many domains, mainly for visually impaired users. The availability of TTS open sources improves access to computers and gives more valuable applications. eSpeak provides support for several languages. It is a tool that provides rules and phoneme files for more than 50 languages, besides, eSpeak is a light, fast, low memory consumption and used in multi-platforms. In this paper, we have explored the possibility to adapt the existing text to speech converters into Arabic language in eSpeak. We attempt to define new text to speech conversion rules, adapting existed phonemes and adding missing phonemes for Arabic under eSpeak. The contributions are quite significant; however, the software's developers will be able to integrated these enhancements within the new version, so that users who have problems with visual impairments or children with special needs will utilise this development of eSpeak. The availability of such support, open new fields to use Arabic in TTS environment, especially for blind persons.

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