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Research on Intelligent English Translation Method Based on the Improved Attention Mechanism Model
- Source :
- Scientific Programming, Vol 2021 (2021)
- Publication Year :
- 2021
- Publisher :
- Hindawi Limited, 2021.
-
Abstract
- The use of neural machine algorithms for English translation is a hot topic in the current research. English translation using the traditional sequential neural framework, which is too poor at capturing long-distance information, has its own major limitations. However, the current improved frameworks, such as recurrent neural network translation, are not satisfactory either. In this paper, we establish an attention coding and decoding model to address the shortcomings of traditional machine translation algorithms, combine the attention mechanism with a neural network framework, and implement the whole English translation system based on TensorFlow, thus improving the translation accuracy. The experimental test results show that the BLUE values of the algorithm model built in this paper are improved to different degrees compared with the traditional machine learning algorithms, which proves that the performance of the proposed algorithm model is significantly improved compared with the traditional model.
- Subjects :
- Translation system
Article Subject
Artificial neural network
Machine translation
business.industry
Computer science
Mechanism (biology)
Translation (geometry)
computer.software_genre
Machine learning
Computer Science Applications
QA76.75-76.765
Recurrent neural network
Computer software
Artificial intelligence
business
computer
Software
Decoding methods
Coding (social sciences)
Subjects
Details
- ISSN :
- 1875919X and 10589244
- Volume :
- 2021
- Database :
- OpenAIRE
- Journal :
- Scientific Programming
- Accession number :
- edsair.doi.dedup.....8702db5bc46bdd56304018e55b3b64ce