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 |
Machine Translation, Rule-based Machine Translation, English Language, Yoruba Language, Computational Rules, Translation System
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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
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
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
@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} }
TY - JOUR T1 - Web-Based English to Yoruba Machine Translation AU - Akinwale O. I. AU - Adetunmbi A. O. AU - Obe O. O. AU - Adesuyi A. T. Y1 - 2015/05/12 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 SP - 154 EP - 159 PB - Science Publishing Group SN - 2330-0221 UR - https://doi.org/10.11648/j.ijll.20150303.17 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 -