Open Source Windows Scientific/Engineering Software

The Arabic Corpus {compiled by Dr. Mourad Abbas ( http://sites.google.com/site/mouradabbas9/corpora ) The corpus Khaleej-2004 contains 5690 documents. It is divided to 4 topics (categories). The corpus Watan-2004 contains 20291 documents organized in 6 topics (categories). Researchers who use these two corpora would mention the two main references: (1) For Watan-2004 corpus ---------------------- M. Abbas, K. Smaili, D. Berkani, (2011) Evaluation of Topic Identification Methods on Arabic Corpora,JOURNAL OF DIGITAL INFORMATION MANAGEMENT,vol. 9, N. 5, pp.185-192. 2) For Khaleej-2004 corpus --------------------------------- M. Abbas, K. Smaili (2005) Comparison of Topic Identification Methods for Arabic Language, RANLP05 : Recent Advances in Natural Language Processing ,pp. 14-17, 21-23 september 2005, Borovets, Bulgary. More useful references to check: ------------------------------------------- https://sites.google.com/site/mouradabbas9/corpora

Arabic files and voices for eSpeak Text to speech system, المنطيق : ملفات اللغة العربية لبرنامج توليد الكلام من النص إسبيك

This project has moved to GitHub.

PADIC (Parallel Arabic DIalectal Corpus) is a multi-dialectal corpus built in the framework of the National Research Project "TORJMAN", led by Scientific and Technical Research Center for the Development of Arabic Language and funded by the Algerian Ministry of Higher Education and Scientific Research. PADIC is composed of 6 dialects: two Algerian dialects (Algiers and Annaba cities), Palestinian, Syrian, Tunisian, Moroccan) and MSA. Mourad Abbas Computational Linguistics Department, crstdla https://sites.google.com/site/mouradabbas9 Publications ----------------- K. Meftouh, S. Harrat, S. Jamoussi, M. Abbas, K. Smaïli, Machine Translation Experiments on PADIC: A Parallel Arabic DIalect Corpus, The 29th Pacific Asia Conference on Language, Information and Computation, PACLIC 2015, Shanghai, 2015. TORJMAN website: ------------------------- https://sites.google.com/site/torjmanepnr/6-corpus

OCR c++ library. Include: contour recognition; vectorisation; matrix letter feature recognition; auto page segmentation and detect rotation; SS3 ASM core; XML base; web-based GUI; 99,6% printed Unicode text recognition; letter base up to 1200 letters.