A Study of Attention Mechanism Models for English Translation Tasks

Xiaoli Yu

doi:10.47297/wspiedWSP2516-250043.20250904

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A Study of Attention Mechanism Models for English Translation Tasks

Volume 9, Issue 4

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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
Vol. 9, Issue 4, Pages: 214-220(2025)
Published：23 April 2025
DOI：10.47297/wspiedWSP2516-250043.20250904
Accepted：

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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：

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

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