THE HISTORICAL DEVELOPMENT AND MODERN PERSPECTIVES OF COMPUTATIONAL LINGUISTICS

Authors

  • Muslikhiddinova Rakhshona AUI teacher

Keywords:

computational linguistics; machine translation; generative grammar; artificial intelligence; neural networks

Abstract

 This article examines and analyzes the main stages in the development of computational linguistics. It explores how the field has evolved from early machine translation experiments in the 1950s to modern neural network models such as GPT and BERT. Each stage—from theoretical and statistical approaches to deep learning innovations—is discussed to show the progress of computational language analysis over time.

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References

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Devlin, J., Chang, M.-W., Lee, K., & Toutanova, K. (2019). BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT 2019). Retrieved from https://aclanthology.org/N19-1423/

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Published

2025-10-14

How to Cite

Muslikhiddinova Rakhshona. (2025). THE HISTORICAL DEVELOPMENT AND MODERN PERSPECTIVES OF COMPUTATIONAL LINGUISTICS. Journal of Applied Science and Social Science, 15(10), 562–565. Retrieved from https://www.internationaljournal.co.in/index.php/jasass/article/view/2074