Design of English Machine Translation Models Based on Deep Neural Network Algorithms
To enhance the accuracy and fluency of English machine translation, this study designed a translation model based on deep neural network algorithms. Utilizing an encoder-decoder architecture with an integrated attention mechanism, the model's ability to capture linguistic context is significant...
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| Published in: | IEEE Information Technology, Networking, Electronic and Automation Control Conference (Online) Vol. 7; pp. 1441 - 1445 |
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| Main Author: | |
| Format: | Conference Proceeding |
| Language: | English |
| Published: |
IEEE
20.09.2024
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| Subjects: | |
| ISSN: | 2693-3128 |
| Online Access: | Get full text |
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| Abstract | To enhance the accuracy and fluency of English machine translation, this study designed a translation model based on deep neural network algorithms. Utilizing an encoder-decoder architecture with an integrated attention mechanism, the model's ability to capture linguistic context is significantly improved. Various aspects such as data preprocessing, model architecture design, training processes, and model optimization were analyzed through comparative studies. The results demonstrate that our model outperforms traditional models on standard datasets, conclusively proving the effectiveness and value of deep learning technology in the field of machine translation. |
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| AbstractList | To enhance the accuracy and fluency of English machine translation, this study designed a translation model based on deep neural network algorithms. Utilizing an encoder-decoder architecture with an integrated attention mechanism, the model's ability to capture linguistic context is significantly improved. Various aspects such as data preprocessing, model architecture design, training processes, and model optimization were analyzed through comparative studies. The results demonstrate that our model outperforms traditional models on standard datasets, conclusively proving the effectiveness and value of deep learning technology in the field of machine translation. |
| Author | Ye, Ying |
| Author_xml | – sequence: 1 givenname: Ying surname: Ye fullname: Ye, Ying email: 550758798@qq.com organization: School of Foreign Languages, Wuhan Business University,Wuhan,China |
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| Snippet | To enhance the accuracy and fluency of English machine translation, this study designed a translation model based on deep neural network algorithms. Utilizing... |
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| StartPage | 1441 |
| SubjectTerms | Analytical models Artificial neural networks Attention mechanisms Convolutional Neural Networks (CNN) Data models Deep learning Deep neural network algorithms English machine translation models Machine translation Solid modeling Solids Training |
| Title | Design of English Machine Translation Models Based on Deep Neural Network Algorithms |
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