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      Automatic meter classification of Kurdish poems

      research-article
      Author(s): , * ,
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      Publication date (Electronic):
      Journal: PLOS ONE
      Publisher: Public Library of Science

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          Abstract

          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 avoiding ambiguity. This paper presents a rule-based method for the automatic classification of the poem meter for the Central Kurdish language also known as Sorani. The metrical system of Kurdish poetry is divided into three classes 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.

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          Meter classification of Arabic poems using deep bidirectional recurrent neural networks

          Maged S. Al-shaibani, Zaid Alyafeai, Irfan S Ahmad (2020)
          Article 0 comments Cited 8 times – based on 0 reviews     Review now
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            • Book: not found

            Introductory phonology.

            B. HAYES, Hayes (2009)
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              Kurdish Dialect Studies

              D. MacKENZIE, D.N. MACKENZIE, MacKenzie, David Neil (1961)
              Book 0 comments Cited 5 times – based on 0 reviews
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                Author and article information

                Contributors
                Aso Mahmudi:
                ORCID: https://orcid.org/0000-0003-2155-4101
                Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: Writing – original draftRole: Writing – review & editing
                Hadi Veisi:
                ORCID: https://orcid.org/0000-0003-2372-7969
                Role: MethodologyRole: Project administrationRole: ResourcesRole: Writing – original draftRole: Writing – review & editing
                Hossein Hassani: Role: Editor
                Journal
                Journal ID (nlm-ta): PLoS One
                Journal ID (iso-abbrev): PLoS One
                Journal ID (publisher-id): plos
                Title: PLOS ONE
                Publisher: Public Library of Science (San Francisco, CA USA )
                ISSN (Electronic): 1932-6203
                Publication date (Electronic): 1 February 2023
                Publication date Collection: 2023
                Volume: 18
                Issue: 2
                Electronic Location Identifier: e0280263
                Affiliations
                [001] Faculty of New Sciences and Technologies, University of Tehran, Tehran, Iran
                University of Kurdistan Hewler, IRAQ
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0003-2155-4101
                https://orcid.org/0000-0003-2372-7969
                Article
                Publisher ID: PONE-D-22-12526
                DOI: 10.1371/journal.pone.0280263
                PMC ID: 9891497
                PubMed ID: 36724172
                SO-VID: 1b7f9836-b608-42ac-8787-6d31c0890ab1
                Copyright © © 2023 Mahmudi, Veisi
                License:

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                Date received : 28 April 2022
                Date accepted : 24 December 2022
                Page count
                Figures: 2, Tables: 14, Pages: 14
                Funding
                The authors received no specific funding for this work.
                Categories
                Subject: Research Article
                Subject: Social Sciences
                Subject: Linguistics
                Subject: Grammar
                Subject: Phonology
                Subject: Syllables
                Subject: Social Sciences
                Subject: Linguistics
                Subject: Phonetics
                Subject: Vowels
                Subject: Biology and Life Sciences
                Subject: Neuroscience
                Subject: Cognitive Science
                Subject: Cognitive Psychology
                Subject: Language
                Subject: Biology and Life Sciences
                Subject: Psychology
                Subject: Cognitive Psychology
                Subject: Language
                Subject: Social Sciences
                Subject: Psychology
                Subject: Cognitive Psychology
                Subject: Language
                Subject: People and Places
                Subject: Population Groupings
                Subject: Ethnicities
                Subject: Asian People
                Subject: Kurdish People
                Subject: Social Sciences
                Subject: Linguistics
                Subject: Phonetics
                Subject: Consonants
                Subject: Social Sciences
                Subject: Linguistics
                Subject: Grammar
                Subject: Phonology
                Subject: Phonemes
                Subject: Computer and Information Sciences
                Subject: Neural Networks
                Subject: Recurrent Neural Networks
                Subject: Biology and Life Sciences
                Subject: Neuroscience
                Subject: Neural Networks
                Subject: Recurrent Neural Networks
                Subject: Biology and Life Sciences
                Subject: Physiology
                Subject: Physiological Parameters
                Subject: Body Weight
                Custom metadata
                Data Availability The test dataset (DOI: 10.5281/zenodo.4079471) is publicly available in a repository at github.com/AsoSoft/Vejinbooks-Poem-Dataset. The source code is publicly accessible in AsoSoft Library’s repository at github.com/AsoSoft/AsoSoft-Library (PoemClassifier.cs).

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                Data availability:
                ScienceOpen disciplines: Uncategorized

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