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Issue title: Impact of Intelligence Methodologies on Education and Training Process
Guest editors: Vijayalakshmi Saravanan
Article type: Research Article
Authors: Conghai, Hu; * | Qianqian, Zhao | Jie, Guo
Affiliations: Cangzhou Normal University, Cangzhou, Hebei, China
Correspondence: [*] Corresponding author. Hu Conghai, Cangzhou Normal University, Cangzhou, Hebei, China. E-mail: huconghai@mailfence.com.
Abstract: The linguistic artificial intelligence teaching model can be assisted by the intelligent speech recognition model. The traditional speech recognition algorithm has certain problems, so it cannot effectively eliminate speech noise. Based on the advantages of the linguistics teaching model, this article combines the linguistics teaching model and the artificial intelligence model to build an artificial intelligence assisted teaching model that can be used for classroom teaching. Moreover, this study improves the traditional algorithm and constructs an artificial intelligence linguistics teaching model based on the improved algorithm. The filtering part of noise includes preliminary filtering of speech signals based on the short-term energy detection method, and further detection and recognition of preliminary filtering speech signals based on the artificial intelligence model detection method. After these two steps of filtering and recognition, the voice file is sent to the client for processing and control. In addition, this study set up a control experiment to analyze the performance of the model. The research results show that the algorithm in this paper has a certain effect.
Keywords: Artificial intelligence, speech model, linguistics, teaching model
DOI: 10.3233/JIFS-189396
Journal: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 3605-3615, 2021
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