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

<p>This paper proposes an automatic grammar error correction model based on an encoder-decoder structure, which is combined with a new business English teaching model that can improve the teaching quality of teachers and enable students to get feedback quickly. The model employs a dual encoder structure and extracts source sentence information through an encoder that is based on the attention mechanism. Meanwhile, a fluency-based data augmentation method is also proposed in order to be able to select sentences with different fluency levels based on the fluency ratio between the target sentence and the source sentence. Finally, a Passive-Aggressive algorithm for candidate word selection has been designed, which can avoid generating repetitive and short-biased English sentences. It has been verified that the total grade of the class that incorporates this paper’s model in business English teaching has increased by 9.3 points on average, with the most obvious improvement in business writing by 3 points, followed by translation by 2.8 points. The proposed teaching model in this paper can enhance students’ comprehensive use of business English.</p>
</abstract>

This paper proposes an automatic grammar error correction model based on an encoder-decoder structure, which is combined with a new business English teaching model that can improve the teaching quality of teachers and enable students to get feedback quickly. The model employs a dual encoder structure and extracts source sentence information through an encoder that is based on the attention mechanism. Meanwhile, a fluency-based data augmentation method is also proposed in order to be able to select sentences with different fluency levels based on the fluency ratio between the target sentence and the source sentence. Finally, a Passive-Aggressive algorithm for candidate word selection has been designed, which can avoid generating repetitive and short-biased English sentences. It has been verified that the total grade of the class that incorporates this paper’s model in business English teaching has increased by 9.3 points on average, with the most obvious improvement in business writing by 3 points, followed by translation by 2.8 points. The proposed teaching model in this paper can enhance students’ comprehensive use of business English.

Research on Digital Business English Teaching Mode under the Background of Big Data Technology

Concord University College, Fujian Normal University

Applied Mathematics and Nonlinear Sciences

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

This paper proposes an automatic grammar error correction model based on an encoder-decoder structure, which is combined with a new business English teaching...

Research on Digital Business English Teaching Mode under the Background of Big Data Technology

Online veröffentlicht: 11. Nov. 2023

Seitenbereich: -

Eingereicht: 07. Feb. 2023

Akzeptiert: 22. Mai 2023

DOI: https://doi.org/10.2478/amns.2023.2.01106

Schlüsselwörter
Grammar correction model, Attention mechanism, Passive-Aggressive algorithm, Decoder, Business English

© 2023 Qian Chen et al., published by Sciendo

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

Research on Digital Business English Teaching Mode under the Background of Big Data Technology

Online veröffentlicht: 11. Nov. 2023

Seitenbereich: -

Eingereicht: 07. Feb. 2023

Akzeptiert: 22. Mai 2023

DOI: https://doi.org/10.2478/amns.2023.2.01106

SchlüsselwörterGrammar correction model, Attention mechanism, Passive-Aggressive algorithm, Decoder, Business English

© 2023 Qian Chen et al., published by Sciendo

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

Schlüsselwörter
Grammar correction model, Attention mechanism, Passive-Aggressive algorithm, Decoder, Business English