A Novel English Translation Model in Complex Environments Using Two-Stream Convolutional Neural Networks. (5th September 2022)
- Record Type:
- Journal Article
- Title:
- A Novel English Translation Model in Complex Environments Using Two-Stream Convolutional Neural Networks. (5th September 2022)
- Main Title:
- A Novel English Translation Model in Complex Environments Using Two-Stream Convolutional Neural Networks
- Authors:
- Zhang, Lijuan
- Other Names:
- kaifa Zhao Academic Editor.
- Abstract:
- Abstract : Although translation is an essential component of learning English, it does not receive the attention it merits in the modern English classroom. Teachers and students primarily emphasize listening, reading, and writing while neglecting the development of translation skills. The English test in China now reflects the fact that there are now very specific requirements for students' translation skills. As a result, we should emphasize developing students' translation skills when teaching them English. The following experimental data can be obtained following the study and experiment on the English translation simulation model based on the two-stream convolutional neural network: English vocabulary and grammar have passing and excellent rates of 90 and 57 percent, respectively, while reading has passing and excellent rates of 69 and 8 percent, respectively. The ability of students to translate into English has significantly improved after using the English translation simulation model based on the two-stream convolutional neural network.
- Is Part Of:
- Journal of environmental and public health. Volume 2022(2022)
- Journal:
- Journal of environmental and public health
- Issue:
- Volume 2022(2022)
- Issue Display:
- Volume 2022, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 2022
- Issue:
- 2022
- Issue Sort Value:
- 2022-2022-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-09-05
- Subjects:
- Environmental health -- Periodicals
Occupational diseases -- Periodicals
Public health -- Periodicals
613.105 - Journal URLs:
- https://www.hindawi.com/journals/jeph/ ↗
- DOI:
- 10.1155/2022/8426460 ↗
- Languages:
- English
- ISSNs:
- 1687-9805
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 23336.xml