About | Contact Us | Register | Login
ProceedingsSeriesJournalsSearchEAI
sis 22(4): 13

Research Article

An automatic scoring method for Chinese-English spoken translation based on attention LSTM

Download532 downloads
Cite
BibTeX Plain Text
  • @ARTICLE{10.4108/eai.13-1-2022.172818,
        author={Xiaobin Guo},
        title={An automatic scoring method for Chinese-English spoken translation based on attention LSTM},
        journal={EAI Endorsed Transactions on Scalable Information Systems},
        volume={9},
        number={4},
        publisher={EAI},
        journal_a={SIS},
        year={2022},
        month={1},
        keywords={Chinese-English spoken translation, attention LSTM, sentence level},
        doi={10.4108/eai.13-1-2022.172818}
    }
    
  • Xiaobin Guo
    Year: 2022
    An automatic scoring method for Chinese-English spoken translation based on attention LSTM
    SIS
    EAI
    DOI: 10.4108/eai.13-1-2022.172818
Xiaobin Guo1,*
  • 1: Zhengzhou Railway Vocational & Technical College
*Contact email: 910675024@qq.com

Abstract

This article has been retracted, and the retraction notice can be found here: http://dx.doi.org/10.4108/eai.8-4-2022.173786. 

In this paper, we propose an automatic scoring method for Chinese-English spoken translation based on attention LSTM. We select semantic keywords, sentence drift and spoken fluency as the main parameters of scoring. In order to improve the accuracy of keyword scoring, this paper uses synonym discrimination method to identify the synonyms in the examinees' answer keywords. At the sentence level, attention LSTM model is used to analyze examinees' translation of sentence general idea. Finally, spoken fluency is scored based on tempo/rate and speech distribution. The final translation quality score is obtained by combining the weighted scores of the three parameters. The experimental results show that the proposed method is in good agreement with the result of manual grading, and achieves the expected design goal compared with other methods.

Keywords
Chinese-English spoken translation, attention LSTM, sentence level
Received
2022-01-06
Accepted
2022-01-12
Published
2022-01-13
Publisher
EAI
http://dx.doi.org/10.4108/eai.13-1-2022.172818

Copyright © 2022 Xiaobin Guo et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.

EBSCOProQuestDBLPDOAJPortico
EAI Logo

About EAI

  • Who We Are
  • Leadership
  • Research Areas
  • Partners
  • Media Center

Community

  • Membership
  • Conference
  • Recognition
  • Sponsor Us

Publish with EAI

  • Publishing
  • Journals
  • Proceedings
  • Books
  • EUDL