Computer Science ›› 2022, Vol. 49 ›› Issue (1): 31-40.doi: 10.11896/jsjkx.210900006

• Multilingual Computing Advanced Technology • Previous Articles     Next Articles

Survey of Mongolian-Chinese Neural Machine Translation

HOU Hong-xu, SUN Shuo, WU Nier   

  1. College of Computer Science,Inner Mongolia University,Hohhot 010021,China
    National & Local Joint Engineering Research Center of Intelligent Information Processing Technology for Mongolian,Hohhot 010021,China
    Inner Mongolia Key Laboratory of Mongolian Information Processing Technology,Hohhot 010021,China
  • Received:2021-09-01 Revised:2021-10-19 Online:2022-01-15 Published:2022-01-18
  • About author:HOU Hong-xu,born in 1972,Ph.D,professor.His main research interests include natural language processing and information retrieval.
  • Supported by:
    Inner Mongolia Autonomous Region Transformation of Scientific and Technological Achievements Project(2019CG028).

Abstract: Machine translation is the process of using a computer to convert one language into another language.With the deep understanding of semantics,neural machine translation has become the most mainstream machine translation method at present,and it has made remarkable achievements in many translation tasks with large-scale alignment corpus,but the effect of translation tasks for some low-resource languages is still not ideal.Mongolian-Chinese machine translation is currently one of the main low-resource machine translation studies in China.The translation of Mongolian and Chinese languages is not simply the conversion between the two languages,but also the communication between the two nations,so it has attracted wide attention at home and abroad.This thesis mainly expounds the development process and research status of Mongolian-Chinese neural machine translation,and then selects the frontier methods of Mongolian-Chinese neural machine translation research in recent years,including data augmentation methods based on unsupervised lear-ning and semi-supervised learning,reinforcement learning,adversarial lear-ning,transfer-learning and neural machine translation methods assisted by pre-training models,etc.,and briefly introduce these methods.

Key words: Adversarial learning, Mongolian-Chinese machine translation, Pre-training model, Reinforcement learning, Semi-supervised/Unsupervised learning, Supervised method, Transfer-learning

CLC Number: 

  • TP391
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