Most of the classic texts in Kurdish literature are poems. Knowing the meter of the poems is helpful for correct reading, a better understanding of the meaning, and avoidance of ambiguity. This paper presents a rule-based method for automatic classification of the poem meter for the Central Kurdish language. The metrical system of Kurdish poetry is divided into three classes of quantitative, syllabic, and free verses. As the vowel length is not phonemic in the language, there are uncertainties in syllable weight and meter identification. The proposed method generates all the possible situations and then, by considering all lines of the input poem and the common meter patterns of Kurdish poetry, identifies the most probable meter type and pattern of the input poem. Evaluation of the method on a dataset from VejinBooks Kurdish corpus resulted in 97.3% of precision in meter type and 96.2% of precision in pattern identification.

中文翻译：

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库尔德诗歌的自动计量器分类

库尔德文学中的大多数经典著作都是诗歌。了解诗歌的计量标准有助于正确阅读，更好地理解其含义以及避免歧义。本文提出了一种基于规则的库尔德中央语言诗表自动分类方法。库尔德诗歌的格律体系分为定量，音节和自由诗歌三类。由于元音长度不是该语言的音素，因此音节的重量和音高识别存在不确定性。所提出的方法会产生所有可能的情况，然后，通过考虑输入诗的所有词句和库尔德诗歌的常见音符样式，来确定输入诗的最可能的音符类型和样式。在VejinBooks Kurdish语料库的数据集上对该方法进行了评估，结果为97。