Applied Mathematics and Nonlinear Sciences
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Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 9, Issue 1


Published
on

May 3, 2024


Pages


DOI

Article

Analysis of Japanese Translation Skills Based on the Perspective of Multimedia Cultural Differences

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Authors

Yang Zhou Affiliation:
ShangHai Jianqiao University, Foreign Language College, Shanghai, 201306, China.


Abstract

This paper screens and calculates the factors affecting the quality of Japanese translation through the gray correlation analysis method. First, the Pearson correlation coefficient is utilized to explore the correlation between each factor and translation quality, and the multicollinearity between the influencing factors is tested. A quadratic test was conducted on the influencing factors using Lasso variable selection and ridge regression methods to eliminate those with linear correlation. On this basis, Japanese translation skills are designed and practiced from the perspectives of naturalized and alienated translation strategies to address cultural differences. The correlation coefficients of the factors affecting the quality of Japanese translation ranged from 0.7017 to 0.9309. The correlation coefficient between translation integrity and average sentence length was 0.491. The overall rating of the translated texts of each student reached a maximum of 97.87 points after using the translation technique. The translation technique in this paper is more effective in Japanese translation, which provides a reference method for the translation strategy under the perspective of cultural differences between China and Japan, and also helps to effectively convey the country’s culture.


Keywords

Gray correlation analysis, Pearson correlation coefficient, Lasso variable, Ridge regression, Translation skill, 35B27


Citation

Zhou, Y. (2024). Analysis of japanese translation skills based on the perspective of multimedia cultural differences. Applied Mathematics and Nonlinear Sciences, 9(1). https://doi.org/10.2478/amns-2024-1030
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