Deep Learning for Natural Language Processing in Bilingual Language

  • Unique Paper ID: 154754
  • PageNo: 335-340
  • Abstract:
  • Existing and emerging technologies aid in the resolution of real-time problems without the need for manual intervention. Code-Switching allows people to socialize with others, learn new languages. This paper discusses various approaches to code-switching, including recurrent neural networks (RNN), support vector machines (SVM), bidirectional encoder representations from Transformers (BERT), and others. As a result, an appropriate method must be chosen to achieve maximum accuracy with solutions to all existing problems with minimal enhancements.

Copyright & License

Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

BibTeX

@article{154754,
        author = {Pooja G  and Gudarada vandana and Usha AH and Muskaan and Pathanjali C},
        title = {Deep Learning for Natural Language Processing in  Bilingual Language },
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {12},
        pages = {335-340},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=154754},
        abstract = {Existing and emerging technologies aid in the resolution of real-time problems without the need for manual intervention. Code-Switching allows people to socialize with others, learn new languages. This paper discusses various approaches to code-switching, including recurrent neural networks (RNN), support vector machines (SVM), bidirectional encoder representations from Transformers (BERT), and others. As a result, an appropriate method must be chosen to achieve maximum accuracy with solutions to all existing problems with minimal enhancements.},
        keywords = {Code-Switching, Speech recognition, Neural Machine Translation, BERT model.},
        month = {},
        }

Cite This Article

G, P., & vandana, G., & AH, U., & Muskaan, , & C, P. (). Deep Learning for Natural Language Processing in Bilingual Language . International Journal of Innovative Research in Technology (IJIRT), 8(12), 335–340.

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