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Test of English vocabulary recognition based on natural language processing and corpus system
- Source :
- Journal of Intelligent & Fuzzy Systems. 40:7073-7084
- Publication Year :
- 2021
- Publisher :
- IOS Press, 2021.
-
Abstract
- English vocabulary recognition has certain applications in both learning and life. The existing English vocabulary recognition model is limited by a variety of factors, which will result in a more complicated recognition process and a low recognition accuracy. In order to improve the effect of English vocabulary recognition, based on natural language processing algorithms and corpus systems, this paper proposes a multi-feature fusion adaptive kernel-related filter tracking algorithm for the problems of kernel-related filtering algorithms. Moreover, based on the KCF algorithm, this paper improves the algorithm from three parts: feature fusion, adaptive change of update rate, and scale detection. In addition, this paper explores whether the vocabulary recognition of different rhythms will affect the reaction time and accuracy of the second language vocabulary recognition when the test subjects are in the experimental conditions with similar characters and different voices. The research results show that the model constructed in this paper performs well in the recognition of English words.
- Subjects :
- Statistics and Probability
business.industry
Computer science
General Engineering
020206 networking & telecommunications
02 engineering and technology
computer.software_genre
Test (assessment)
Artificial Intelligence
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Artificial intelligence
business
English vocabulary
computer
Natural language processing
Subjects
Details
- ISSN :
- 18758967 and 10641246
- Volume :
- 40
- Database :
- OpenAIRE
- Journal :
- Journal of Intelligent & Fuzzy Systems
- Accession number :
- edsair.doi...........4d99be832b63bb512179ef5cb3078f76