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Research on Machine Translation Model Based on Neural Network

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Communications, Signal Processing, and Systems (CSPS 2018)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 517))

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Abstract

Machine Translation is an important part of Natural Language Processing. The model based on convolution neural network and attention mechanism (Fcnn model), which was proposed by Facebook in 2017, has been successful. We use this Fcnn model as the baseline model of this subject, and on the base of this model, we try to improve it by the combination of bytes pair encoding method, model ensemble method. In this issue, we use Bilingual Evaluation Understudy (BLEU) as a criterion to measure the quality of translation. After testing, these methods can improve the translation quality of the model. Finally, the overall translation quality increased from 0.28 of the baseline Fcnn model to 0.32.

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Author information

Authors and Affiliations

  1. Shanghai Jiao Tong University, Shanghai, China

    Zhuoran Han & Shenghong Li

Authors
  1. Zhuoran Han
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  2. Shenghong Li
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Corresponding author

Correspondence to Zhuoran Han .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, University of Texas at Arlington, Arlington, TX, USA

    Qilian Liang

  2. School of Information and Communication Engineering, Dalian University of Technology, Dalian, China

    Xin Liu

  3. School of Information Science and Technology, Dalian Maritime University, Dalian, China

    Zhenyu Na

  4. College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin, China

    Wei Wang

  5. College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin, China

    Jiasong Mu

  6. College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin, China

    Baoju Zhang

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© 2020 Springer Nature Singapore Pte Ltd.

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Han, Z., Li, S. (2020). Research on Machine Translation Model Based on Neural Network. In: Liang, Q., Liu, X., Na, Z., Wang, W., Mu, J., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2018. Lecture Notes in Electrical Engineering, vol 517. Springer, Singapore. https://doi.org/10.1007/978-981-13-6508-9_31

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  • DOI: https://doi.org/10.1007/978-981-13-6508-9_31

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-6507-2

  • Online ISBN: 978-981-13-6508-9

  • eBook Packages: EngineeringEngineering (R0)

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