English to Kurdish Rule-based Machine Translation System
DOI:
https://doi.org/10.21928/uhdjst.v2n2y2018.pp32-39Keywords:
MT, SMT, Apertuim, Morphological, Evaluation, BilingualAbstract
In this paper we present a machine translation system developed to translate simple English sentences to Kurdish. The system is based on the (apertuim) free open source engine that provides the environment and the required tools to develop a machine translation system. The developed system is used to translate some as simple sentence, compound sentence, phrases and idioms from English to Kurdish. The resulting translation is then evaluated manually for accuracy and completeness compared to the result produced by the popular (inKurdish) English to Kurdish machine translation system. The result shows that our system is more accurate than inkurdish system. This paper contributes towards the ongoing effort to achieve full machine-based translation in general and English to Kurdish machine translation in specific.
References
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[29]Hossein Hassani. 2017. Kurdish Interdialect Machine Translation. Proceedings of the fourth workshop on NLP for similar languages, varieties and dialects (VarDial), pages 63-72, 2017.
[30] Wiechetek, Linda. 2008. Rule-based MT approaches such as Apertium and GramTrans. Universitetet i Tromsø (Norway) 21.10.2008.
[2] Tanveer Siddiqui and U.S Tiwary. 2010. Natural language processing and Information Retrieval. Oxford University Press. Second impression 2010.
[3] Chang Liu, Daniel Dahlmeier, and Hwee Tou Ng. 2011. Better evaluation metrics lead to better machine translation. In Proceedings of EMNLP.
[4] Apertuim. 2018. About Apertuim. [online] available: https://www.apertium.org/index.eng.html?dir=eng-spa#translation [accessed on 7/8/2018].
[5] Warren Weaver. 1955. Translation. Machine Translation of Languages: Fourteen Essays.
[6] Jose´ B. Marin˜o, Rafael E. Banchs,Josep M. Crego, Adria` de Gispert, Patrik Lambert,Jose´ A. R. Fonollosa, and Marta R. Costa-jussa`.2006. N-gram based machine translation. Computational Linguistics, 32(4):527–549.
[7] Peter F Brown, Vincent J Della Pietra, Stephen A Della Pietra, and Robert L Mercer. 1993. The mathematics of statistical machine translation: Parameter estimation. Computational linguistics, 19(2):263–311. [8] Franz Josef Och. 2003. Minimum error rate training for statistical machine translation. In Proceedings of ACL.
[9] Philipp Koehn, Franz Josef Och, and Daniel Marcu. 2003. Statistical phrase-based translation. In Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology-Volume 1, pages 48–54. Association for Computational Linguistics.
[10] Philipp Koehn and Christof Monz. 2005. Shared task: Statistical machine translation between European languages. In Proceedings of the ACL Workshop on Building and Using Parallel Texts.
[11] David Chiang. 2005. A hierarchical phrase-based model for statistical machine translation. In Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics (ACL), pages 263–270. [12] Arul Menezes, Kristina Toutanova, and Chris Quirk. 2006. Microsoft research treelet translation system: Naacl 2006 europarl evaluation. In Proceedings of WMT.
[13] Philipp Koehn, Hieu Hoang, Alexandra Birch, Chris Callison-Burch, Marcello Federico, Nicola Bertoldi, Brooke Cowan, Wade Shen, Christine Moran, Richard Zens, et al. 2007b. Moses: Open source toolkit for statistical machine translation. In Proceedings of the 45th annual meeting of the ACL on interactive poster and demonstration sessions, pages 177–180.Association for Computational Linguistics.
[14] Young Sook Hwang, Andrew Finch, and Yutaka Sasaki. 2007. Improving statistical machine translation using shallow linguistic knowledge. Computer Speech and Language, 21(2):350–372.
[15] F. Sa´nchezMart´inez and M. L. Forcada. 2009. Inferring shallow-transfer machine translation rules from small parallel corpora. Journal of Artificial Intelligence Research, 34:605–635. [16] Maxim Khalilov and Jose´ A. R. Fonollosa. 20 11. Syntax-based reordering for statistical machine translation. Computer Speech and Language, 25(4):761–788. [17] Sergei Nirenburg. 1989. Knowledge based machine translation. Machine Translation, 4(1):5–24.
[18] Michael Carl and Andy Way. 2003. Recent advances in example-based machine translation. [19] Philipp Koehn and Kevin Knight. 2009. Statistical machine translation, November 24. US Patent 7,624,005. [20] Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2014. Neural machine translation by jointly learning to align and translate. CoRR, abs/1409.0473. [21] KyungHyun Cho, Bart van Merrienboer, Dzmitry Bahdanau, and Yoshua Bengio.2014. On the properties of neural machine translation: Encoder-decoder approaches. CoRR,abs/1409.1259. [22] Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2014. Neural machine translation by jointly learning to align and translate. CoRR, abs/1409.0473.
[23] Krzysztof Wolk and Krzysztof Marasek. 2015. Neural-based machine translation for medical text domain. Based on european medicines agency leaflet texts. Procedia Computer Science, 64:2 – 9. Conference on{ENTERprise} Information Systems/International Conference on Project MANagement/Conference on Health and Social Care Information Systems and Technologies, CENTERIS/ProjMAN / {HCist} 2015 October 7-9, 2015.
[24] Safeen Ghafour. 2011. “Speeculate” [online] available: https://www.kurditgroup.org/sites/default/files/speekulate_0.pdf [accessed on 4/8/2018].
[25] inkurdish Translator. 2013. [Online]. available https://inkurdish.com/ [accessed on 4/8/2018].
[26] Ekurd Daily - Editorial Staff . 2016. “Google Translate adds support for Kurdish language”.[online] Available: https://ekurd.net/google-translate-kurdish-language-2016-02-18 [accessed on 4/8/2018].
[27] TRANSLATORS WITHOUT BORDERS. 2016. “Translators without Borders developed the world’s first crisis-specific machine translation system for Kurdish languages” available: https://translatorswithoutborders.org/translators-without-borders-develops-worlds-first-crisis-specific-machine-translation-system-kurdish-languages/ [acceded on 4/8/2018].
[28] Kanaan M.Kaka-kHan and Fatima jalal. 2017. Evaluation of inkurdish machine translation system. presented in the 4th International Scientific Conference of University of Human Development, April, 2017. JUHD / Vol. 3, No. 2, June 2017: pp862-868.
[29]Hossein Hassani. 2017. Kurdish Interdialect Machine Translation. Proceedings of the fourth workshop on NLP for similar languages, varieties and dialects (VarDial), pages 63-72, 2017.
[30] Wiechetek, Linda. 2008. Rule-based MT approaches such as Apertium and GramTrans. Universitetet i Tromsø (Norway) 21.10.2008.
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Published
2018-09-02
How to Cite
Kaka-Khan, kanaan mikael. (2018). English to Kurdish Rule-based Machine Translation System. UHD Journal of Science and Technology, 2(2), 32–39. https://doi.org/10.21928/uhdjst.v2n2y2018.pp32-39
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