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<p>This paper discusses the construction of “interactive” English translation teaching mode in the background of the Internet, and analyzes the application of neural machine translation model in improving the effect of translation teaching. The research adopts Word2vec algorithm to train word vectors, combines neural network language model and encoder-decoder structure, and constructs Transformer model and CNN+Transformer model to improve translation efficiency and quality. The translation experiments on sentences of different lengths show that the models perform better in short sentence translation. The experimental results show that the proposed model outperforms the traditional model in terms of BLEU value, and the best translation effect is found in test set 1, where the BLEU value is improved by 10.6 and 11.7 compared with that of the baseline model and the CNN model, respectively. The “interactive” teaching mode designed with POA theory significantly outperforms the traditional teaching mode regarding students’ lexical, grammatical and semantic translation quality. The “interactive” English translation teaching with neural translation model can effectively improve the quality of translation teaching and students’ learning effect.</p>
</abstract>

This paper discusses the construction of “interactive” English translation teaching mode in the background of the Internet, and analyzes the application of neural machine translation model in improving the effect of translation teaching. The research adopts Word2vec algorithm to train word vectors, combines neural network language model and encoder-decoder structure, and constructs Transformer model and CNN+Transformer model to improve translation efficiency and quality. The translation experiments on sentences of different lengths show that the models perform better in short sentence translation. The experimental results show that the proposed model outperforms the traditional model in terms of BLEU value, and the best translation effect is found in test set 1, where the BLEU value is improved by 10.6 and 11.7 compared with that of the baseline model and the CNN model, respectively. The “interactive” teaching mode designed with POA theory significantly outperforms the traditional teaching mode regarding students’ lexical, grammatical and semantic translation quality. The “interactive” English translation teaching with neural translation model can effectively improve the quality of translation teaching and students’ learning effect.

The Construction of “Interactive” English Translation Teaching Mode in the Background of Internet

Applied Mathematics and Nonlinear Sciences

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

This paper discusses the construction of “interactive” English translation teaching mode in the background of the Internet, and analyzes the application of...

The Construction of “Interactive” English Translation Teaching Mode in the Background of Internet

Publicado en línea: 26 feb 2024

Páginas: -

Recibido: 17 ene 2024

Aceptado: 23 ene 2024

DOI: https://doi.org/10.2478/amns-2024-0667

Palabras clave
Neural network language modeling, BLEU-valued translation assessment, Application of POA theory in teaching

© 2024 Xiaoming Li, published by Sciendo

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

The Construction of “Interactive” English Translation Teaching Mode in the Background of Internet

Publicado en línea: 26 feb 2024

Páginas: -

Recibido: 17 ene 2024

Aceptado: 23 ene 2024

DOI: https://doi.org/10.2478/amns-2024-0667

Palabras claveNeural network language modeling, BLEU-valued translation assessment, Application of POA theory in teaching

© 2024 Xiaoming Li, published by Sciendo

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

Palabras clave
Neural network language modeling, BLEU-valued translation assessment, Application of POA theory in teaching