云南省人工智能重点实验室

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论文作者：	Zhiqiang Yu,Zhengtao Yu ,Yantuan Xian,Yuxin Huang,Junjun Guo.
论文名称：	Improving Chinese-Vietnamese Neural Machine Translation with Linguistic Differences
论文发表刊物：	ACM Transactions on Asian and Low-Resource Language Information Processing
论文发表时间：	2022
卷号页码：
论文描述：
收录情况：	SCI Indexed
论文摘要：
We present a simple, efficient data augmentation approach for boosting Chinese-Vietnamese neural machine translation performance by leveraging the linguistic difference between the two languages. We first define the formalized representation of modifier symmetry, which is one of the most representative linguistic differences between Chinese and Vietnamese. We then propose and test two data augmentation strategies for leveraging the linguistic difference, which can be integrated naturally with different translation models. Results indicate that both strategies can introduce linguistic rules to boost translation accuracy. Tests on Chinese-Vietnamese benchmarks show significant accuracy improvements. To facilitate studies in this domain, we also release an open-source toolkit1 with flexible implementation for Chinese-Vietnamese linguistic difference tagging.
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