A Study of Attention Mechanism Models for English Translation Tasks

Xiaoli Yu

doi:10.47297/wspiedWSP2516-250043.20250904

PDF
导出
分享
收藏
专辑

A Study of Attention Mechanism Models for English Translation Tasks

9卷第4期

浏览量: 0 Downloads: 0

A Study of Attention Mechanism Models for English Translation Tasks
A Study of Attention Mechanism Models for English Translation Tasks
English College, Zhejiang Yuexiu University, Shaoxing, Zhejiang, China, 312000
2025年9卷第4期页码：214-220
纸质出版日期：2025-04-23
DOI：10.47297/wspiedWSP2516-250043.20250904
Accepted：

Scan QR Code

(2025). A Study of Attention Mechanism Models for English Translation Tasks. 国际教育与发展（英文版）, 9(4), 214-220.

Yu Xiaoli.A Study of Attention Mechanism Models for English Translation Tasks[J].Journal of International Education and Development,2025,09(04):214-220.
(2025). A Study of Attention Mechanism Models for English Translation Tasks. 国际教育与发展（英文版）, 9(4), 214-220. DOI： 10.47297/wspiedWSP2516-250043.20250904.

Yu Xiaoli.A Study of Attention Mechanism Models for English Translation Tasks[J].Journal of International Education and Development,2025,09(04):214-220. DOI： 10.47297/wspiedWSP2516-250043.20250904.

摘要

Abstract

As deep learning is widely used in natural language processing

neural machine translation (NMT) has become mainstream. The attention mechanism offers a new way to enhance translation quality. This paper explores an attention - mechanism model for English translation. By comparing the basic Seq2Seq model and the attention - added model in English - to - Chinese translation tasks

it assesses translation - quality improvement. A simulation experiment using the WMT 2014 English - Chinese parallel corpus is designed

and the model is analyzed with BLEU

ROUGE

and TER. Results show that the attention - based model outperforms the basic one in BLEU and ROUGE scores and has lower TER scores

indicating the attention mechanism effectively boosts translation quality and accuracy. In summary

the attention - based translation model proposed here has good performance and application potential in English translation tasks.

关键词

Keywords

references

Zuo Jia . Research on the design of corpus Machine translation System based on compression algorithm and Self-attention mechanism model [J ] . Automation & Instrumentation , 2024 ( 6 ): 194 - 198 .

Zhang Juling . Analysis of combining fuzzy algorithm with improved attention mechanism in AI translation [J ] . Automation & Instrumentation , 2024 ( 8 ): 223 - 227 .

Han Xue , Wang Zhanghui , Zhang Hanting . Chinese-english machine translation model based on Attention-directed graph Convolutional networks [J ] . Computer and Digital Engineering , 2019 , 49 ( 12 ): 7 .

Song Kaitao , Lu Jianfeng . Neural machine translation based on mixed self-attention mechanism . Journal of Chinese Information Processing , 2023 , 37 ( 9 ): 38 - 45 .

Cao Heling , Liu Yu , Han Dong . Software defect automatic repair method based on self-attention mechanism neural machine translation [J ] . Acta Electronica Sinica , 2019 , 52 ( 3 ): 945 - 956 .

Zheng Yixiong , Zhu Junguo , Yu Zhengtao . The role of part-of-speech information in neural machine translation . Journal of Chinese Information Processing , 2023 , 37 ( 12 ): 26 - 35 .

LIU Jiao . Application of improved Transformer model in machine translation field: a case study of Multi30k German-English dataset [D ] . Capital University of Economics and Business , 2022 .

Ma Houli , Dong Ling , Wang Jian , et al . An end-to-end speech translation method based on multi-feature fusion . Journal of Chinese Information Processing , 2019 , 38 ( 10 ): 35 - 45 .

Hou Qiang , Hou Ruili . Neural machine translation: Insights and prospects [J ] . Journal of Foreign Languages , 2021 ( 5 ): 54 - 59 .

Liu Junpeng , Huang Kaiyu , Li Jiuyi , et al . Neural machine Translation based on multi-coverage model [J ] . Journal of Software , 202 , 33 ( 3 ): 12 .

Yang Hao , Xu Qing , Shao Bangli , et al . An end-to-end model-based approach to Chinese syntax analysis [J ] . Journal of Suzhou University of Science and Technology (Natural Science Edition) , 2021 , 038 ( 002 ): 77 - 84 .

Ge Tengfei . Research on Situational translation of Intelligent Software Engineering based on Attention mechanism and Bidirectional LSTM coding model [J ] . Automation & Instrumentation , 2024 ( 7 ): 256 - 261 .

Liu Junpeng , Huang Kaiyu , Li Jiuyi , et al . Neural machine Translation based on multi-coverage model [J ] . Journal of Software , 202 , 33 ( 3 ): 12 .

Chen Xi , Chen Aobo . Neural machine translation based on mask matrix BERT attention mechanism [J ] . Modern Electronic Technique , 2019 , 46 ( 21 ): 111 - 116 .

ZHOU Leyuan , Zhang Jianhua , Yuan Tiantian , et al . Multilevel attention mechanism fusion of sequence-to-sequence Chinese continuous sign language recognition and translation [J ] . Computer Science , 2002 , 49 ( 9 ): 7 .

Chen Yi , Xie Chen . Research on Cross-modal entity Information Fusion in AI Translation [J ] . Automation & Instrumentation , 2024 ( 8 ): 247 - 250 .

Ren Yanqing . Application of intelligent technology in Machine translation system [J ] . 2024 ( 5 ): 254 - 255 . (in Chinese) .

Xue Quantian , Li Junhui , Gong Zhengxian , et al .

Qiao Wanjun , Zhao Qing . Research on Speech Automatic Correction System based on end-to-end English Translator [J ] . Automation & Instrumentation , 2023 ( 3 ): 240 - 244 .

文章被引用时，请邮件提醒。

Submit

On the Impact of Cultural Construction and Cultural Default on English Translation

An Empirical Study on School-enterprise Cooperation in China: Translation Workshop as a New Teaching Mode

Related Author

Ting Yang

Can YANG

Related Institution

College of International Studies and Education, Tongren University

Jinhua polytechnic

⁰