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Automatic meter classification of Kurdish poems.

Aso Mahmudi¹, Hadi Veisi¹

¹Faculty of New Sciences and Technologies, University of Tehran, Tehran, Iran.

|February 1, 2023

Summary

This study introduces an automated method for classifying Kurdish poem meters in Sorani, enhancing understanding and accuracy. The rule-based system achieves high precision in identifying both meter type and specific patterns.

Area of Science:

Computational Linguistics
Digital Humanities
Natural Language Processing

Background:

Kurdish literature predominantly features poetry, making metrical analysis crucial for accurate interpretation.
Understanding poetic meter aids in correct reading, deeper comprehension, and disambiguation of meaning.
Existing challenges in Sorani (Central Kurdish) poetry analysis include uncertainties in syllable weight due to non-phonemic vowel length.

Purpose of the Study:

To develop and evaluate a rule-based method for the automatic classification of poem meters in the Central Kurdish language (Sorani).
To address the ambiguities in meter identification caused by the language's phonemic vowel length.
To improve the accessibility and analysis of classical Kurdish poetic texts.

Main Methods:

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A rule-based approach was designed for automatic meter classification of Sorani poems.
The method generates all potential metrical scenarios.
It analyzes all lines of a poem in conjunction with established Kurdish poetic meter patterns to determine the most likely classification.

Main Results:

The automated system achieved high precision in identifying the meter type.
Precise classification of specific metrical patterns was also demonstrated.
Evaluation on the VejinBooks Kurdish corpus yielded 97.3% precision for meter type and 96.2% for pattern identification.

Conclusions:

The proposed rule-based method effectively automates the classification of Kurdish poem meters in Sorani.
This approach offers a reliable solution for analyzing poetic meter, overcoming linguistic challenges.
The high precision rates indicate the method's potential for digital humanities and computational linguistics applications in Kurdish literature.