Abstract
The prominent Arabic Domestic changes have influenced the usage of the Arabic dialects among Arabs communications, which was, previously, limited on daily activities inside their own territories the role of the Modern Standard. Arabic MSA as an official Arabic language started to be diminished, since the Arabic dialects play a greater role than using it during the daily activities. The continuity of using these dialects whether in media or writing may eliminate the dominance of MSA as an official form of Arabic language in the Arab world. Besides, comprehending the Arabic language by non-native speakers, as well as, processing machine translations became a sophisticated process that requires harder effort. Accordingly, a requirement of language processing to interact with the permanent development of the dialects and to flourish the standard Arabic became imperative. Thus, it is planned to built a Hybrid Machine translation system (AlMoFseH) to translate the different Arabic dialects by using the MSA as a pivot. This research is a part of this project which emphasizes on developing a transfer-based system that transfers the Egyptian Arabic dialect EGY used in social media to MSA. For that purpose, a lexical database of 3k words presenting Egyptian Arabic dialect was built. Different texts extracted from Social media were used as a main resource of the database. The system consists of three components: disambiguation of the morphological analysis output using Naive Bayesian learning, a rule based transfer system and a dictionary look up system. The evaluation revealed a high accuracy of the system’s performance, since 92.7% of the test data was transferred correctly.
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Hamada, S., Marzouk, R.M. (2018). Developing a Transfer-Based System for Arabic Dialects Translation. In: Shaalan, K., Hassanien, A., Tolba, F. (eds) Intelligent Natural Language Processing: Trends and Applications. Studies in Computational Intelligence, vol 740. Springer, Cham. https://doi.org/10.1007/978-3-319-67056-0_7
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