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Web-Based English to Yoruba Machine Translation

Received: 26 March 2015     Accepted: 1 May 2015     Published: 12 May 2015
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Abstract

The growth of globalization in the world today has increased the rate at which people interact and integrate, thereby increasing the level of international integration from interchange of world views, products, ideas and other aspects of culture. Language differences therefore pose a major barrier to smooth running of these processes. Therefore there is need for existence of system that will help translate between languages. English is a West Germanic language which has become the lingual Franca in Nigeria and 53 other countries. Therefore vital information are written and spoken in English language in Nigeria. Meanwhile,Yoruba language is lagerly spoken in Nigeria with over 40 million speakers in the south-western part of the country and also in parts of Benin republic. This research deals with the translation of English text to Yoruba text using rule based method. Twenty two rules were formulated for the translation which is specified using context free grammar. A bilingual dictionary dataset containing English words and the corresponding translation in Yoruba language was used. The research model was implemented with ASP.net and C# programming languages which has been hosted on http://www.naijatranslate.com. The translator was evaluated to have accuracy of 90.5%.

Published in International Journal of Language and Linguistics (Volume 3, Issue 3)
DOI 10.11648/j.ijll.20150303.17
Page(s) 154-159
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2015. Published by Science Publishing Group

Keywords

Machine Translation, Rule-based Machine Translation, English Language, Yoruba Language, Computational Rules, Translation System

References
[1] Chux O. (2013, August 8). Punch Newspaper. Retrieved from http://www.punchng.com/feature/gradually-nigerian-languages-are-dying/
[2] Abiola O.B., Adetunmbi A.O., Fasiku A. I. & Olatunji K. A. (2014). A Web-Based English to Yoruba noun-phrases Machine Translation System. International Journal of English and Literature,5(3),71-78.http//dx.doi.org/10.5897/IJEL2013.0472.
[3] Adeoye O., (2012). A Web-Based English to Yoruba Noun-Phrase Machine Translation. (Masters Thesis). Federal University of Technology, Akure, Nigeria.
[4] Eludiora, S. (2013). Development of an English to Yoruba machine Translation system. (Doctoral dissertation) Obafemi Awolowo University, Ile-Ife, Nigeria.
[5] Haiying L., Arthur C. G. & Zhaiqiang C. (2014). Comparison of Google Translation with Human Translation: Proceedings of the Twenty-seventh International Florida Artificial Intelligence Research Society Conference, University of Memphis, Institute of Intelligent system, Memphis, USA.
[6] Stephen H. & Carmen P. S. (2010). Translation and the Internet: Evaluating the Quality of free Online Machine Translators, Quaderns. Rev. trad. 17, 197 – 209.
[7] Henderson F., (2010). Giving a Voice to More languages on Google Translate, The official Google Translate blog. Available: http://googletranslate.blogspot.com/2010/05/giving-voice-to-more-languages-on.html.
[8] Mahsa, M. (2012). English - Persian Phrase - Based Statistical Machine Translation: Enhanced Models, Search and Training. (Doctoral dissertation). Massey University, Albany (Auckland), New Zealand.
[9] Yetunde, O. F. and Omonayin, I. (2012). Using Statistical Machine Translation As A language Translation tool for understanding Yoruba. EIE’s 2nd International Conference on.Computing Energy, Networking, Robotics and Telecommunications. eieCon2012. 86-91. http://dx.doi.org/10.13140/2.1.3522.8454.
Cite This Article
  • APA Style

    Akinwale O. I., Adetunmbi A. O., Obe O. O., Adesuyi A. T. (2015). Web-Based English to Yoruba Machine Translation. International Journal of Language and Linguistics, 3(3), 154-159. https://doi.org/10.11648/j.ijll.20150303.17

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    ACS Style

    Akinwale O. I.; Adetunmbi A. O.; Obe O. O.; Adesuyi A. T. Web-Based English to Yoruba Machine Translation. Int. J. Lang. Linguist. 2015, 3(3), 154-159. doi: 10.11648/j.ijll.20150303.17

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    AMA Style

    Akinwale O. I., Adetunmbi A. O., Obe O. O., Adesuyi A. T. Web-Based English to Yoruba Machine Translation. Int J Lang Linguist. 2015;3(3):154-159. doi: 10.11648/j.ijll.20150303.17

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  • @article{10.11648/j.ijll.20150303.17,
      author = {Akinwale O. I. and Adetunmbi A. O. and Obe O. O. and Adesuyi A. T.},
      title = {Web-Based English to Yoruba Machine Translation},
      journal = {International Journal of Language and Linguistics},
      volume = {3},
      number = {3},
      pages = {154-159},
      doi = {10.11648/j.ijll.20150303.17},
      url = {https://doi.org/10.11648/j.ijll.20150303.17},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijll.20150303.17},
      abstract = {The growth of globalization in the world today has increased the rate at which people interact and integrate, thereby increasing the level of international integration from interchange of world views, products, ideas and other aspects of culture. Language differences therefore pose a major barrier to smooth running of these processes. Therefore there is need for existence of system that will help translate between languages. English is a West Germanic language which has become the lingual Franca in Nigeria and 53 other countries. Therefore vital information are written and spoken in English language in Nigeria. Meanwhile,Yoruba language is lagerly spoken in Nigeria with over 40 million speakers in the south-western part of the country and also in parts of Benin republic. This research deals with the translation of English text to Yoruba text using rule based method.  Twenty two rules were formulated for the translation which is specified using context free grammar. A bilingual dictionary dataset containing English words and the corresponding translation in Yoruba language was used. The research model was implemented with ASP.net and C# programming languages which has been hosted on http://www.naijatranslate.com. The translator was evaluated to have accuracy of 90.5%.},
     year = {2015}
    }
    

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    T1  - Web-Based English to Yoruba Machine Translation
    AU  - Akinwale O. I.
    AU  - Adetunmbi A. O.
    AU  - Obe O. O.
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    PY  - 2015
    N1  - https://doi.org/10.11648/j.ijll.20150303.17
    DO  - 10.11648/j.ijll.20150303.17
    T2  - International Journal of Language and Linguistics
    JF  - International Journal of Language and Linguistics
    JO  - International Journal of Language and Linguistics
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    PB  - Science Publishing Group
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    AB  - The growth of globalization in the world today has increased the rate at which people interact and integrate, thereby increasing the level of international integration from interchange of world views, products, ideas and other aspects of culture. Language differences therefore pose a major barrier to smooth running of these processes. Therefore there is need for existence of system that will help translate between languages. English is a West Germanic language which has become the lingual Franca in Nigeria and 53 other countries. Therefore vital information are written and spoken in English language in Nigeria. Meanwhile,Yoruba language is lagerly spoken in Nigeria with over 40 million speakers in the south-western part of the country and also in parts of Benin republic. This research deals with the translation of English text to Yoruba text using rule based method.  Twenty two rules were formulated for the translation which is specified using context free grammar. A bilingual dictionary dataset containing English words and the corresponding translation in Yoruba language was used. The research model was implemented with ASP.net and C# programming languages which has been hosted on http://www.naijatranslate.com. The translator was evaluated to have accuracy of 90.5%.
    VL  - 3
    IS  - 3
    ER  - 

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Author Information
  • Computer Science Department, Federal University of Technology, Akure, Nigeria

  • Computer Science Department, Federal University of Technology, Akure, Nigeria

  • Computer Science Department, Federal University of Technology, Akure, Nigeria

  • Computer Science Department, Federal University of Technology, Akure, Nigeria

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