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Research Article

Design and Analysis of Language Translator

Somaanath M U1 Subash T S2 Vijaya Lakshmanan M3
123 Computer Science and Engineering, Bannari Amman Institute of Technology,TN, India.

Published Online: November-December 2022

Pages: 40-46

Cite this article

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References

1. Luong MT, Pham H, Manning CD. Effective approaches to attention-based neural machine translation. arXiv preprint arXiv:1508.04025.
2015 Aug 17.
2. Yang S, Wang Y, Chu X. A survey of deep learning techniques for neural machine translation. arXiv preprint arXiv:2002.07526. 2020
Feb 18.
3. Bahdanau, D. ,Cho, K. Bengio , Y. (2014). Neural machine translation by jointly learning to align and translate. arXiv preprint
arXiv:1409.0473. [4].
4. Britz, D., Goldie, A.,Luong, M.T., Le, Q. (2017). Massive exploration of neural machine translation architectures. arXiv preprint
arXiv:1703.03906.
5. Raffel C, Shazeer N, Roberts A, Lee K, Narang S, Matena M, Zhou Y, Li W, Liu PJ. Exploring the limits of transfer learning with a
unified text- to-text transformer. J. Mach. Learn. Res.. 2020 Jun;21(140):1-67.
6. Vaswani A, Shazeer N, Parmar N, Uszkoreit J, Jones L, Gomez AN, Kaiser Ł, Polosukhin I. Attention is all you need.
Advances in neural information processing systems. 2017;30.

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