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Morphology Model and Segmentation for Old Turkic Language

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Computational Collective Intelligence (ICCCI 2021)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12876))

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Abstract

Old Turkic language is the basis of all modern Turkic languages. Its study is very important for Turkic peoples who possess modern Turkic languages. This is important both from a historical point of view and for the study of modern issues of neural machine translation, issues of the linguistic distance of modern Turkic languages from their progenitor. This paper proposes the development of a computational model of the morphology of Old Turkic language based on the CSE (Complete Set of Endings) – model of morphology and a study on this basis of the issue of morphological segmentation of the texts of Old Turkic language, which will subsequently be used for neural machine translation of Old Turkic language into modern Turkic languages. Since most of the modern Turkic languages, except for the Turkish language, belong to low-resource languages, the issues of developing computational models of morphology, developing models, algorithms and software for processing Turkic languages are relevant.

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Author information

Authors and Affiliations

  1. Al-Farabi Kazakh National University, Almaty, Kazakhstan

    Dinara Zhanabergenova & Ualsher Tukeyev

Authors
  1. Dinara Zhanabergenova
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  2. Ualsher Tukeyev
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Editor information

Editors and Affiliations

  1. Wrocław University of Science and Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. Democritus University of Thrace, Kimmeria, Xanthi, Greece

    Lazaros Iliadis

  3. University of Piraeus, Piraeus, Greece

    Ilias Maglogiannis

  4. Wrocław University of Science and Technology, Wrocław, Poland

    Bogdan Trawiński

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Zhanabergenova, D., Tukeyev, U. (2021). Morphology Model and Segmentation for Old Turkic Language. In: Nguyen, N.T., Iliadis, L., Maglogiannis, I., Trawiński, B. (eds) Computational Collective Intelligence. ICCCI 2021. Lecture Notes in Computer Science(), vol 12876. Springer, Cham. https://doi.org/10.1007/978-3-030-88081-1_47

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  • DOI: https://doi.org/10.1007/978-3-030-88081-1_47

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  • Online ISBN: 978-3-030-88081-1

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