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Research Article | Open Access |

Development of a Recurrent Neural Network Model for English to Yorùbá Machine Translation

Author 1: Adebimpe Esan Author 2: John Oladosu Author 3: Christopher Oyeleye Author 4: Ibrahim Adeyanju Author 5: Olatayo Olaniyan Author 6: Nnamdi Okomba Author 7: Bolaji Omodunbi Author 8: Opeyemi Adanigbo
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 11, No. 5 · Published 2020 · Cited by 13

DOI: https://doi.org/10.14569/IJACSA.2020.0110574

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Abstract

This research developed a recurrent neural network model for English to Yoruba machine translation. Parallel corpus was obtained from the English and Yoruba bible corpus. The developed model was tested and evaluated using both manual and automatic evaluation techniques. Results from manual evaluation by ten human evaluators show that the system is adequate and fluent. Also, results from automatic evaluation shows that the developed model has decent and good translation as well as higher accuracy because it has better correlation with human judgment.

Keywords

Recurrent tokenizer corpus translation evaluation correlation

How to Cite this Article

Esan, A., Oladosu, J., Oyeleye, C., Adeyanju, I., Olaniyan, O., Okomba, N., Omodunbi, B., & Adanigbo, O. (2020). Development of a Recurrent Neural Network Model for English to Yorùbá Machine Translation. International Journal of Advanced Computer Science and Applications, 11(5). https://doi.org/10.14569/IJACSA.2020.0110574

Esan, Adebimpe, et al.. "Development of a Recurrent Neural Network Model for English to Yorùbá Machine Translation." International Journal of Advanced Computer Science and Applications, vol. 11, no. 5, 2020, https://doi.org/10.14569/IJACSA.2020.0110574.

@article{Esan2020,
  title     = {Development of a Recurrent Neural Network Model for English to Yorùbá Machine Translation},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {11},
  number    = {5},
  year      = {2020},
  publisher = {The Science and Information Organization},
  author    = {Adebimpe Esan and John Oladosu and Christopher Oyeleye and Ibrahim Adeyanju and Olatayo Olaniyan and Nnamdi Okomba and Bolaji Omodunbi and Opeyemi Adanigbo},
  doi       = {10.14569/IJACSA.2020.0110574},
  url       = {https://doi.org/10.14569/IJACSA.2020.0110574}
}

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