A Semi-supervised Learning-Based Method for Correcting Translation Accuracy of Literature Works

DOI

10.2991/978-94-6463-024-4_98How to use a DOI?

Keywords

Semi supervised learning; Literary; Literary translation; Translation accuracy; Translation correction

Abstract

This paper studies the accuracy correction method of literary translation based on semi supervised learning, so as to improve the accuracy of Literary translation and reduce the translation error rate. Based on the word vector of recurrent neural network, the data preprocessing and feature extraction of translation of Literary works are realized by constructing a word alignment and segmentation model. Based on T F - I D F algorithm, the translation grammatical features of Literary works are extracted, and K-means clustering algorithm is used to detect the accuracy features. Based on semi supervised learning, mistranslation features are identified, and translation accuracy correction of Literary works is realized through semantic feature analysis. The results show that this method can detect the mistranslation features in the grammar feature sample set. The number of mistranslation features detected is almost the same as the actual number of mistranslation categories in the corresponding data set, and the comprehensive detection performance is high; We can distinguish the mistranslated grammar from the correct grammar through grammar mistranslation correction, and the overall correction accuracy is higher than 98%.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Hongzhu Jiang
PY  - 2022
DA  - 2022/12/12
TI  - A Semi-supervised Learning-Based Method for Correcting Translation Accuracy of Literature Works
BT  - Proceedings of the 2022 2nd International Conference on Education, Information Management and Service Science (EIMSS 2022)
PB  - Atlantis Press
SP  - 937
EP  - 950
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-024-4_98
DO  - 10.2991/978-94-6463-024-4_98
ID  - Jiang2022
ER  -