English Speech Feature Recognition-Based Fuzzy Algorithm and Artificial Intelligent

It is necessary to study the application of digital technology in English speech feature recognition. This paper combines the actual needs of English speech feature recognition to improve the digital algorithm. Moreover, this paper combines fuzzy algorithm to analyze English speech features, analyze...

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Published in:Wireless communications and mobile computing Vol. 2022; no. 1
Main Authors: Miao, Yuji, Liu, Haiying, Gu, Shan
Format: Journal Article
Language:English
Published: Oxford Hindawi 2022
John Wiley & Sons, Inc
Subjects:
Algorithms
Clustering
Communication
Computers
Data mining
Feature recognition
Information superhighway
Multimedia
Neural networks
Noise
Office automation
R&D
Research & development
Signal processing
Speech
Speech recognition
Time-frequency analysis
ISSN:1530-8669, 1530-8677
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Abstract It is necessary to study the application of digital technology in English speech feature recognition. This paper combines the actual needs of English speech feature recognition to improve the digital algorithm. Moreover, this paper combines fuzzy algorithm to analyze English speech features, analyzes the shortcomings of traditional algorithms, proposes the fuzzy digitized English speech recognition algorithm, and builds an English speech feature recognition model on this basis. In addition, this paper conducts time-frequency analysis on chaotic signals and speech signals, eliminates noise in English speech features, improves the recognition effect of English speech features, and builds an English speech feature recognition system based on digital means. Finally, this paper conducts grouping experiments by inputting students’ English pronunciation forms and counts the results of the experiments to test the performance of the system. The research results show that the method proposed in this paper has a certain effect.
AbstractList It is necessary to study the application of digital technology in English speech feature recognition. This paper combines the actual needs of English speech feature recognition to improve the digital algorithm. Moreover, this paper combines fuzzy algorithm to analyze English speech features, analyzes the shortcomings of traditional algorithms, proposes the fuzzy digitized English speech recognition algorithm, and builds an English speech feature recognition model on this basis. In addition, this paper conducts time-frequency analysis on chaotic signals and speech signals, eliminates noise in English speech features, improves the recognition effect of English speech features, and builds an English speech feature recognition system based on digital means. Finally, this paper conducts grouping experiments by inputting students’ English pronunciation forms and counts the results of the experiments to test the performance of the system. The research results show that the method proposed in this paper has a certain effect.
Author Miao, Yuji
Liu, Haiying
Gu, Shan
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Copyright Copyright © 2022 Yuji Miao et al.
Copyright © 2022 Yuji Miao et al. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
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SubjectTerms Algorithms
Clustering
Communication
Computers
Data mining
Feature recognition
Information superhighway
Multimedia
Neural networks
Noise
Office automation
R&D
Research & development
Signal processing
Speech
Speech recognition
Time-frequency analysis
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