Analysis and evaluation on the quality of news text machine translation based on neural network

  • Liu TingtingEmail author
  • Xiao Mengyu


Machine translation quality estimation is an important task in natural language processing. Unlike traditional automatic machine translation evaluation methods, the quality of machine translation is evaluated by the translation quality estimation method without using manual reference translation. In view of the fact that the feature extraction of current sentence-level machine translation quality estimation relies heavily on linguistic analysis, which leads to insufficient generalization ability and restricts the performance of subsequent support vector regression algorithm, it is proposed to extract the features of sentence vectors by using contextual word prediction model and matrix decomposition model in deep learning, and combine them with the features of recurrent neural network language model to improve the correlation between automatic estimation of translation quality and manual evaluation. The experimental results on WMT15 and WMT16 translation quality estimation subtask data sets show that the performance statistics of the method of extracting sentence vector features by adopting context word prediction model are consistently superior to that of the traditional Quest method and continuous space language model sentence vector feature extraction method. It reveals that the proposed feature extraction method not only requires no linguistic analysis, but also significantly improves the effect of translation quality estimation.


Neural network Text machine Translation quality Analysis and evaluation 



Teaching Research Project of Fuyang Normal University No.2012JYXM44; Scientific Research Project of Fuyang Normal University 2012WBZX05.


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© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.College of Foreign LanguagesFuyang Normal UniversityFuyangChina
  2. 2.College of Information and EngineeringFuyang Normal UniversityFuyangChina

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