Abstract
In this paper, we improved the final accuracy of statistic alignment of phrase-based statistic machine translation (PBSMT) and introduced the improved alignment result into NMT. Moreover, we investigated syntax reordering and data augmentation for improving SMT alignments, which eventually leads to better NMT performance. The experiment results show that applying our approach to Mongolian-Chinese translation demonstrates promising improvements. With annotation alignment and compared to NMT baseline, we obtained up to 2.98 BLEU improvement on the low-resource language pair Mongolian-Chinese.
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