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Abstract

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The Kazakh Language Requires Reform of its Writing

Affiliation

Affiliation

    Doctor of Technical Sciences, Professor of Department of Artificial Intelligence Technology, L. N. Gumilyov Eurasian National University, Astana, Kazakhstan

Abstract

The article provides information about modern problems of writing the Kazakh language, the importance of its role and development in the context of mass digitization using artificial intelligence technologies and computational linguistics methods. The incorrectness of the current alphabet of the Kazakh language based on the Cyrillic alphabet is proved in connection with the inclusion of Cyrillic letters in it, denoting phonemes that are not included in its sound structure. The necessity of reforming the Kazakh writing by replacing the incorrect alphabet is substantiated. Errors and contradictions are shown in the approved version of the Kazakh alphabet based on the Latin alphabet, as well as the alphabet proposed as a replacement for the approved one, in which some previous errors are repeated. In both cases, no analysis and clarification of the sound system of the Kazakh language, which is the basis of any alphabet, is carried out. In this study, to clarify the sound system of the Kazakh language, experiments were carried out to determine the articulation and acoustic features of Kazakh sounds with the help the computer programs used for many natural languages. In the articulation analysis, special attention was paid to vowels, which give rise to various contradictions in the Kazakh letter. It is proposed to use a new classification of vowels according to four binary features, rather than the traditional classification according to three binary features. Acoustic analysis uses the method of formant analysis, which is aimed at identifying certain formants in the spectrogram. The formant is obtained using a spectrograph. Quantitatively, the formants correspond to the maxima in the speech spectrum and usually appear on spectrograms as horizontal bands. After determining the composition and classification of the sound system of the Kazakh language, two variants of the alphabet based on the Latin alphabet are proposed: the first one is based on the Turkish alphabet using diacritical marks; the second is based on the English alphabet using digraphs. The second option offers ways to solve problems that arise when using digraphs. In conclusion, information is provided on the ongoing and ongoing work in Kazakhstan related to the creation of smart systems in the Kazakh language based on the methods and technologies of artificial intelligence and computational linguistics, the results of which are reflected in the list of sources.

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References

    1. Kazakh language. 2024. https://en.wikipedia.org/wiki/Kazakh_language.
    2. Law of the Republic of Kazakhstan Concerning languages in the Republic of Kazakhstan, № 151-1 of 11 July, 1997. 2020. https://online.zakon.kz/Document/?doc_id=1049836&pos=12;-32#pos=12;-32
    3. Old Turkic script. 2024. https://en.wikipedia.org/wiki/Old_Turkic_script
    4. Hasanov Z. Issyk Inscription. Turkic World. http://s155239215.onlinehome.us/turkic/30_Writing/IssykInscription/HasanovZ2015IssykInscriptionEn.htm
    5. Kazakh writing. Wikipedia. 2024. https://ru.wikipedia.org/wiki/Казахская_письменность
    6. Kazakh alphabets. Wikipedia. 2024. https://en.wikipedia.org/wiki/Kazakh_alphabets
    7. International Phonetic Alphabet. 2024. https://en.wikipedia.org/wiki/International_Phonetic_Alphabet
    8. Kazakh alphabets. Wikipedia. 2024. https://en.wikipedia.org/wiki/Kazakh_alphabets
    9. Hayward K. 2000. Experimental Phonetics, Harlow, UK.
    10. Phonetic analysis. kaz-tili.kz. https://kaz-tili.kz/su_fonraz.htm
    11. Boolean algebra. 2023. https://en.wikipedia.org/wiki/Boolean_algebra
    12. Yessenbayev Z, Karabalayeva M, Sharipbayev A. Formant analysis and mathematical model of Kazakh vowels. In 2012 UKSim 14th International Conference on Computer Modelling and Simulation. 2012; 427-431.
    13. Sharipbaev AA, Bekmanova GT, Buribayeva AK, Yergesh BZ, Mukanova AS, Kaliyev AK. Semantic neural network model of morphological rules of the agglutinative languages. In The 6th International Conference on Soft Computing and Intelligent Systems, and The 13th International Symposium on Advanced Intelligence Systems. 2012; 1094-1099.
    14. Yergesh B, Mukanova A, Sharipbay A, Bekmanova G, Razakhova B. Semantic hyper-graph based representation of nouns in the Kazakh language. Computacion y Sistemas. 2014; 18(3):627-635.
    15. Barlybayev A, Sabyrov T, Sharipbay A, Omarbekova A. Data Base Processing Programs with Using Extended Base Semantic Hypergraph. In Recent Advances in Information Systems and Technologies. 2017; 1:5; 28-37.
    16. Sharipbayev A, Bekmanova G, Yergesh B, Mukanova A, Buribayeva A. Semantic retrieval of information in the Kazakh language in elibraries. Journal of International Scientific Publications: Educational Alternatives. 2014; 108-115.
    17. Mukanova A, Yergesh B, Bekmanova G, Razakhova B, Sharipbay A. Formal models of nouns in the Kazakh language. Leonardo Electronic Journal of Practices and Technologies. 2014; 25: 264-273.
    18. Sharipbay AA, Bekmanova G, Yergesh B, Mukanova A. Synchronized liner tree for morphological analysis and generation of the Kazakh language. In Proceedings of the international conference “Turkic languages processing”, TurkLang. 2014; 113-117.
    19. Zhetkenbay L, Sharipbay A, Bekmanova G, Kamanur U. Ontological modeling of morphological rules for the adjectives in Kazakh and Turkish languages. Journal of Theoretical and Applied Information Technology. 2016; 91(2):257-263.
    20. Omarbekova A, Sharipbay A, Barlybaev A. Generation of test questions from RDF files using PYTHON and SPARQL. In Journal of Physics: Conference Series. 2017; 806:1; 012009.
    21. Yergesh B, Bekmanova G, Sharipbay A, Yergesh M. Ontology-based sentiment analysis of kazakh sentences. In Computational Science and Its Applications–ICCSA 2017: 17th International Conference, Trieste, Italy. 2017; 17: 669-677.
    22. Kozhirbayev Z, Erol BA, Sharipbay A, Jamshidi M. Speaker recognition for robotic control via an iot device. In 2018 World Automation Congress (WAC). 2018; 1-5.
    23. Bekmanova G, Yelibayeva G, Aubakirova S, Dyussupova N, Sharipbay A, Nyazova R. Methods for analyzing polarity of the Kazakh texts related to the terrorist threats. In Computational Science and Its Applications–ICCSA 2019: 19th International Conference, Saint Petersburg, Russia. 2019; 717-730.
    24. Zulkhazhav A, Kozhirbayev Z, Yessenbayev Z, Sharipbay A. Kazakh text summarization using fuzzy logic. Computación y Sistemas. 2019; 23(3):851-859.
    25. Yergesh B, Bekmanova G, Sharipbay A. Sentiment analysis of Kazakh text and their polarity. In Web Intelligence. 2019; 17:1; 9-15.
    26. Yelibayeva G, Mukanova A, Sharipbay A, Zulkhazhav A, Yergesh B, Bekmanova G. Metalanguage and knowledgebase for Kazakh morphology. In Computational Science and Its Applications–ICCSA 2019: 19th International Conference, Saint Petersburg, Russia. 2019; 693-706.
    27. Sharipbay A, Razakhova B, Mukanova A, Yergesh B, Yelibayeva G. Syntax parsing model of Kazakh simple sentences. In Proceedings of the Second International Conference on Data Science, E-Learning and Information Systems. 2019; 1-5.

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