The Fundamental and Strategic Linguistic Data, the Key for the Reciprocal Complementation of Technology and Artificial Intelligence in Machine Translation

Document Type : research article

Author

Abstract

This question about the possibility of inventing a system more capable than humans in performing behaviors has always been on the table, even before the advent of powerful computers and artificial intelligence algorithms.

Today, we confide in the fact that the idea of exploiting artificial intelligence, and facilitating its application in multiple areas of science, has been a necessity; however, the implementations of this achievement were not provided by mechanics. This field was not a proper context for creating the reciprocal complementation of linguistics, logic, statistics, and mathematics to revolve around it and could not provide the required agility to employ its achievements in accomplishing Machine Translation. On the other hand, with the advent of a phenomenon known as digital, not only did the procedures of formal logic turn into mathematical logic and that of the mathematics turned into modern mathematics, but also new trends were established in this regard and developed rapidly in linguistic researches properly relevant to digital contexts. After a brief introduction to the topic and its theoretical framework, this paper tries to determine how these achievements have been accomplished and intends to elaborate upon the future prospects with respect to the highlighted methods. While presenting his personal experiences in this area, the author of this paper emphasizes establishing a diverse institutional resource in modern linguistics. In his view, future achievements and accomplishments are due to developing the latest and fundamentally required data in linguistics as an interdisciplinary field of knowledge in order to gain practical achievements.

Keywords

Main Subjects

References

  1. 1- جولیا اس فالک. (1377). زبان شناسی و زبان. مترجم خسرو غلامعلی زاده. چاپ پنجم. مشهد: موسسه چاپ و انتشارات آستان قدس رضوی.

    2- دبیر مقدم، محمد. (1383). زبان شناسی نظری. تهران: نشر سمت.

    3- راسل. رابرت. (1383). هوش مصنوعی.  مترجم رامین رهنمون. تهران: نشر ناقوس.

        4- ولی‌پور، علیرضا. بررسی بُعد زبان‌شناختی ترجمه ماشینی و معرفی اجمالی علوم مرتبط با آن . پژوهش زبانهای خارجی، شماره 1386 بهار , 37

       5- ولی‌پور، علیرضا. مقایسه و بررسی برخی نظامهای ترجمه ماشینی روسی و غربی . پژوهش زبانهای خارجی، شماره 42 ,زمستان 1386

    6- باطنی، محمدرضا. (1354). مسائل زبان‌شناسی نوین، تهران: نشر آگاه.

    7- دبیر مقدم، محمد. (1383). زبان‌شناسی نظری، تهران: انتشارات سمت.

    8- دیتل، هاروی. (1385). راهنمای جامع برنامه‌نویسان. مترجم بهرام پاشایی. چاپ یازدهم. تهران: انتشارات جهان نو.

    9- راسل، جی. اس. (1383). هوش مصنوعی، رهیافتی مدرن. مترجم رامین رهنمون وآناهیتا هماوندی. چاپ سوم. تهران: انتشارات ناقوس.

    10- ساغرونیان، سید جلیل. (1369). فرهنگ اصطلاحات زبان‌شناسی، مشهد: انتشارات نما.

    Resources

    1. Falk, Julia S. (1998). Linguistics and language. Trans. Gholam Ali Zadeh, k. Ed. 5th . Astan Print.
    2. Dabir Moghaddam, M. (2004). Theoretical linguistics. Tehran: Samt.
    3. Russell. Robert. (2004). Artificial intelligence. Tr. Rahnamoun, R. Tehran: Naghoos Press.
    4. Valipour, A. An examination of the linguistic dimension of machine translation and a brief introduction of relevant sciences. Foreign Languages Research, No 37, Spring 2007.
    5. Valipour, A. A comparison and review of some Russian and Western machine translation systems. Foreign Languages Research, No. 42, Winter 2007.
    6. Bateni, M. (1976). Modern linguistic issues, Tehran: Agah.
    7. Dabir Moghaddam, M. (2004). Theoretical linguistics, Tehran: Samt.
    8. Deitel, Harvey M. (2006). XML How to Program. Tr. Pashaie, B. Ed. 11th. Tehran: Jahanno.
    9. Russell, J. S. (2004). Artificial intelligence, modern approach. Tr. Rahnamoun, R and A, Hamavandi. Ed. 3rd. Tehran: Naghoos Press.
    10. Sagharvanian, S. J. (1990). The dictionary of linguistic terms, Mashhad: Nama.
    11. Apresyan, Yu.D. (1987). Linguistic support in the third generation automatic translation system. USSR Academy of Sciences, preprint of the scientific council on “the problem of Cybernetics”. М.
    12. Yngve, V. (1965). The value of machine translation research. – ITY, М.

    13.Kuzmin O. I (2019 ) Collegium Linguisticum -Prospects For The Development Of Automated Translation Systems Using The Specifics Of Pre- And Post-Editing (By The Material Of The English Language), 133-142

    1. 14. Marchuk, Yu.N. (1983). Machine translation problems. М.: Наука.
    2. 15., I.A. (1989). To the construction of a working model of the language “Sense-Text”. M.
    3. Mironenko A.B, Omelchenko P.A. (2016) Problems Of Machine Translation Seriya 2, 1193-1195
    4. Panasenkov N.A. (2019) Evolution Of Machine Translation: From Babbage’s Analytical Engine To Neural Networks : 9-13
    5. Rarenko Maria B (2021) Machine Translation as a challenge. 1. Inion of The Russian Academy of Sciences (Ras), Moscow, Russia: 117-126
    6. 19. Popov, E. V. (1990). E.V. (1990). Artificial intelligence book 1 radio and communication. М.
    7. Baiwei Liu ( 2021) The Future Of Machine Translation And Human Translation In The Belt And Road InitiativeVestnik Moskovskogo Universiteta. Seriya 2, 79-88
    8. Barkhudarov T.I. New lexicography. — M .: VTsP, 1995.—183 с.
Journal of Foreign Language Research
Volume 11, Issue 3
November 2021
Pages 541-555

Files

Share

How to cite

Statistics