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Issue title: Complex evolutionary artificial intelligence in cognitive digital twinning
Guest editors: Neal Wagner, Sundhararajan, Le Hoang Son and Meng Joo
Article type: Research Article
Authors: Lanlan, Pan; * | Liangyu, Hu | Zhengya, Li
Affiliations: School of Public Foundation, Jiangsu Vocational College of Medicine, Yancheng, Jiangsu, China
Correspondence: [*] Corresponding author. Pan Lanlan, School of Public Foundation, Jiangsu Vocational College of Medicine,Yancheng, Jiangsu, China. E-mail: [email protected].
Abstract: English part-of-speech intelligent recognition is the scientific and technological basis for the development of intelligent speech systems. The difficulty in the current English speech recognition system lies in the recognition of English parts of speech. In order to improve the effect of English part-of-speech recognition, this study builds the language rules and morphological models of English morphological forms based on machine learning algorithms. Moreover, this study proposes a stemming extraction algorithm and a syllable division algorithm based on English characteristic rules. By studying basic phrases in English, this study analyzes the compositional structure of phrases, and determines the basic phrase structure and composition rules of English such as noun, verb, and adjective. In addition, this research studies the basic English phrase recognition algorithm based on the rule method and the analysis of basic phrase ambiguity resolution. Finally, this study designs a control experiment to analyze the performance of the algorithm proposed in this paper model and confirm the classification algorithm. The research results show that the algorithm proposed in this paper has a certain practical effect.
Keywords: Machine learning, prediction algorithm, English, part-of-speech recognition, algorithm improvement
DOI: 10.3233/JIFS-189236
Journal: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2409-2419, 2021
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