Abstract
This paper presents the development of bidirectional English-Oromiffa machine translation system using a hybrid of rule-based and statistical approaches. Since English and Oromiffa have different sentence structures, we implement syntactic reordering with the purpose of making the structure of source sentences similar to the structure of target sentences. Accordingly, reordering rules are developed for simple, interrogative and complex English and Oromiffa sentences. Two groups of experiments are conducted by using purely statistical approach and hybrid approach. The Oromiffa-English SMT yields a BLEU score of 41.50% where as English-Oromiffa SMT has a BLEU score of 32.39%. After applying local reordering rules, the system is improved to provide a BLEU score of 52.02% and 37.41% for Oromiffa-English and English-Oromiffa translations, respectively.
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Daba, J., Assabie, Y. (2014). A Hybrid Approach to the Development of Bidirectional English-Oromiffa Machine Translation. In: Przepiórkowski, A., Ogrodniczuk, M. (eds) Advances in Natural Language Processing. NLP 2014. Lecture Notes in Computer Science(), vol 8686. Springer, Cham. https://doi.org/10.1007/978-3-319-10888-9_24
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DOI: https://doi.org/10.1007/978-3-319-10888-9_24
Publisher Name: Springer, Cham
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