Using natural language processing for analyzing Arabic poetry rhythm

One from the most difficult tasks for Natural Language Processing (NLP) is to analyze poetry, which uses a different genre of language than that considered by computer-based techniques. Therefore, computational analysis is an interesting task when we use NLP in poetry, but it is also challenging. There are a number of researchers that entered this field from NLP and they got promising results using mathematical analysis for poetry, including rhythm analysis. In this paper we focused on providing solution for automating the rhythm detection of the Arabic poems and finding the number of rhythm for each verse in poem and the total percentage for each rhythm in all verses of poem, additional to other characteristics for the Arabic poem like percentage of mobile letter in Arabic “harf mutaharrik”, and The quiescent letter, in Arabic “harf sakin”, In spite of the number of studies in the computational analysis of poetry, we think it needs more, not only to make a better understanding of domain but also in developing applications, considering different literary tastes and the psychological effects, to give a recommendation to the readers and in plagiarism detection[1].