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Using natural language processing for analyzing Arabic poetry rhythm

机译:利用自然语言处理分析阿拉伯语诗歌节奏

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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].
机译:来自自然语言处理(NLP)最困难的任务的一个是分析诗歌,它使用不同类型的语言而不是由基于计算机的技术考虑的语言。因此,当我们在诗歌中使用NLP时,计算分析是一个有趣的任务,但它也是具有挑战性的。有许多研究人员从NLP进入了这一领域,并且他们对诗歌的数学分析具有有前途的结果,包括节奏分析。在本文中,我们专注于提供解决阿拉伯语诗的节奏检测的解决方案,并在诗歌中找到每节经文的节奏数量和所有节奏的总百分比,额外的阿拉伯语诗的其他特征阿拉伯语“Harf Mutaharrik”的移动信的百分比,以及阿拉伯语“Harf Sakin”的静态信,尽管研究了诗歌的计算分析中的研究数量,但我们认为它需要更多,不仅要更好地了解域名,而且在开发应用中,考虑到不同的文学品味和心理影响,向读者和抄袭检测提供建议[1]。

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