Abstract
We apply several word reordering techniques to a Bangla-English Statistical Machine Translation (SMT) system. We evaluate the approaches through their impact on the BLEU score for the phrase-based Bangla-English SMT system. According to the experimental results, automatic reordering rules have the most significant impact on the BLEU score. We also provide a new test set with multiple references between Bangla and English for SMT evaluation purposes and evaluate the reordering approaches on the extended test set.
This research was partially supported by a discovery grant from NSERC, Canada.
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Roy, M., Popowich, F. (2010). Word Reordering Approaches for Bangla-English Statistical Machine Translation. In: Farzindar, A., Kešelj, V. (eds) Advances in Artificial Intelligence. Canadian AI 2010. Lecture Notes in Computer Science(), vol 6085. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13059-5_29
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DOI: https://doi.org/10.1007/978-3-642-13059-5_29
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