Comparative Study of the Most Useful Arabic-supporting Natural Language Processing and Deep Learning Libraries

Natural Language Processing (NLP) is a key area of Artificial Intelligence (AI) that plays a critical role in many intelligent applications. To work on NLP, users can choose different Libraries, depending on their familiarity with a particular programming language. In this paper, we are focusing on Python and Java programming languages because of their libraries'richness in the Arabic Natural Language Processing (ANLP) and deep learning (DL) specifically. This paper presents a comparative study of some well-known ANLP and DL libraries considered to be the most valuable Arabic-supporting Python and Java libraries that can suitably deal with the specificities of the Arabic language. We will first focus on some libraries that are most commonly used in NLP tasks, namely NLTK, Gensim, OpenNLP, CoreNLP and GATE. Then, we will present some open-source DL libraries that are considered to be the most powerful DL libraries for ANLP, including TensorFlow, Theano, Keras and DeepLearning4j. These libraries simplify complex jobs and make data integration much easier with fewer codes and in less time.