Malay-Corpus-Enhanced Indonesian-Chinese Neural Machine Translation

  • Wuying Liu
  • Lin WangEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 986)


Due to the lack of structured language resources, low-resource language machine translation often faces difficulties in cross-language semantic paraphrasing. In order to solve the problem of low-resource machine translation from Indonesian to Chinese, a cognate-parallel-corpus-based expanding method of language resources is proposed, and an improved neural machine translation model is trained by the Malay-corpus-enhanced corpus. The improved model can achieve a comparable result as that of Google in the experiment of Indonesian-Chinese machine translation. The experimental results also show that the morphological similarity and semantic equivalence between the languages are very effective computational features to improve the performance of neural machine translation for low-resource languages.


Corpus enhancement Neural machine translation Morphological overlap ratio Corpus transfer ratio Low-resource language 



The research is supported by the Key Project of State Language Commission of China (No. ZDI135-26), the Natural Science Foundation of Guangdong Province (No. 2018A030313672), the Featured Innovation Project of Guangdong Province (No. 2015KTSCX035), the Bidding Project of Guangdong Provincial Key Laboratory of Philosophy and Social Sciences (No. LEC2017WTKT002), and the Key Project of Guangzhou Key Research Base of Humanities and Social Sciences: Guangzhou Center for Innovative Communication in International Cities (No. 2017-IC-02).


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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Laboratory of Language Engineering and ComputingGuangdong University of Foreign StudiesGuangzhouChina
  2. 2.School of Information Science and TechnologyJiujiang UniversityJiujiangChina
  3. 3.Xianda College of Economics and HumanitiesShanghai International Studies UniversityShanghaiChina

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