Reordering is of essential importance problem for phrase based statistical machine translation (SMT). In this paper, we propose an approach to automatically learn reordering rules as preprocessing step based on a dependency parser in phrase-based statistical machine translation for English to Vietnamese. We used dependency parsing and rules extracting from training the features-rich discriminative classifiers for reordering source-side sentences. We evaluated our approach on English-Vietnamese machine translation tasks, and showed that it outperform the baseline phrase-based SMT system.
CITATION STYLE
Tran, V. H., Vu, H. T., Nguyen, V. V., & Nguyen, M. L. (2018). A classifier-based preordering approach for English-Vietnamese statistical machine translation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9624 LNCS, pp. 74–87). Springer Verlag. https://doi.org/10.1007/978-3-319-75487-1_7
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