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The Practice of Machine Translation in the Enhancement of English Reading Comprehension in Multicultural Environments

Juan Yu

Juan Yu

International Education and Humanities School, Xi’AN KEDAGAOXIN UniversityXi’an, China
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Yu, Juan
  
Mar 17, 2025
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Published Online: Mar 17, 2025
Received: Oct 17, 2024
Accepted: Feb 14, 2025
DOI: https://doi.org/10.2478/amns-2025-0234
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© 2025 Juan Yu, published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.

Figure 1.

Art-decoder structure
Art-decoder structure

Figure 2.

Machine translation model containing Embedding layer
Machine translation model containing Embedding layer

Figure 3.

The cyclic neural network based on the attention mechanism
The cyclic neural network based on the attention mechanism

Figure 4.

Neural machine translation process platform workflow path
Neural machine translation process platform workflow path

Figure 5.

The loss value and the bleu value curve
The loss value and the bleu value curve

Figure 6.

Pre-experiment the students read the distribution of the scores
Pre-experiment the students read the distribution of the scores

Figure 7.

After the experiment, the students read the distribution of the scores
After the experiment, the students read the distribution of the scores

Figure 8.

Results of questionnaire survey results
Results of questionnaire survey results

English reading comprehension level test results descriptive statistics

Teaching experiment Pre-test Post-test
Class CK (mean) T (mean) CK (mean) T (mean)
Reading score 56.82 56.6 62.38 70.6
Standard error 4.137 3.648 5.267 4.563
P 0.951 0.000

The regression prediction of students’ reading comprehension ability

Variable Reading comprehension
Correlation coefficient Relative error Significance
Gender 0.016 0.002 0.075
Age 0.029 0.007 0.081
Majors 0.005 0.001 0.143
Teacher level 0.007 0.001 0.107
Teaching model 0.078 0.003 0.095
Machine translation 0.199*** 0.024 0.000
R2 0.261
F 17.596
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English
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