<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>With the development of globalization, there is an increasing demand for English-Chinese translation talents in the country and society. In this paper, a text classifier based on multilayer perceptron is proposed, an MLP structure containing two layers of feedforward neural network is designed for the characteristics of English-Chinese translation corpus, the training samples are selected with text height mainly below 60 pixels, and the best sliding window of 13×13 is selected by comparison, supplemented by the smoothing method of mathematical morphology. The constructed MLP-based information-based teaching model is then applied to teaching English-Chinese translation in colleges and universities and is mainly evaluated in terms of student evaluation and teaching effectiveness. There were 28.48 percentage points more English-Chinese translation students who thought the class was more interesting than the original, while 20.56% and 20.50% more students evaluated the class as more helpful and less helpful, respectively. The average score of English-Chinese translation students increased by 15.88% compared to the original one through the comparison test between traditional and informational teaching modes. The MLP-based informatization teaching can mobilize students’ enthusiasm to participate in English-Chinese translation learning, strengthen the guidance of translation methods, and improve students’ translation levels.</p>
</abstract>

With the development of globalization, there is an increasing demand for English-Chinese translation talents in the country and society. In this paper, a text classifier based on multilayer perceptron is proposed, an MLP structure containing two layers of feedforward neural network is designed for the characteristics of English-Chinese translation corpus, the training samples are selected with text height mainly below 60 pixels, and the best sliding window of 13×13 is selected by comparison, supplemented by the smoothing method of mathematical morphology. The constructed MLP-based information-based teaching model is then applied to teaching English-Chinese translation in colleges and universities and is mainly evaluated in terms of student evaluation and teaching effectiveness. There were 28.48 percentage points more English-Chinese translation students who thought the class was more interesting than the original, while 20.56% and 20.50% more students evaluated the class as more helpful and less helpful, respectively. The average score of English-Chinese translation students increased by 15.88% compared to the original one through the comparison test between traditional and informational teaching modes. The MLP-based informatization teaching can mobilize students’ enthusiasm to participate in English-Chinese translation learning, strengthen the guidance of translation methods, and improve students’ translation levels.

An informative teaching model of English-Chinese translation in universities based on the perceptual machine model

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

With the development of globalization, there is an increasing demand for English-Chinese translation talents in the country and society. In this paper, a text...

An informative teaching model of English-Chinese translation in universities based on the perceptual machine model

Online veröffentlicht: 04. Sept. 2023

Seitenbereich: -

Eingereicht: 27. Okt. 2022

Akzeptiert: 15. März 2022

DOI: https://doi.org/10.2478/amns.2023.2.00285

Schlüsselwörter
MLP model, English-Chinese translation, Text classification, Information-based teaching, Neural network

© 2023 Shuang Xue et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

An informative teaching model of English-Chinese translation in universities based on the perceptual machine model

Online veröffentlicht: 04. Sept. 2023

Seitenbereich: -

Eingereicht: 27. Okt. 2022

Akzeptiert: 15. März 2022

DOI: https://doi.org/10.2478/amns.2023.2.00285

SchlüsselwörterMLP model, English-Chinese translation, Text classification, Information-based teaching, Neural network

© 2023 Shuang Xue et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
MLP model, English-Chinese translation, Text classification, Information-based teaching, Neural network