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Human-computer interactive physical education teaching method based on speech recognition engine technology
With the advent of the era of artificial intelligence, speech recognition engine technology has a profound impact on social production, life, education, and other fields. Voice interaction is the most basic and practical type of human-computer interaction. To build an intelligent and automatic physi...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9339716/ https://www.ncbi.nlm.nih.gov/pubmed/35923977 http://dx.doi.org/10.3389/fpubh.2022.941083 |
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author | Sang, Yunpeng Chen, Xingquan |
author_facet | Sang, Yunpeng Chen, Xingquan |
author_sort | Sang, Yunpeng |
collection | PubMed |
description | With the advent of the era of artificial intelligence, speech recognition engine technology has a profound impact on social production, life, education, and other fields. Voice interaction is the most basic and practical type of human-computer interaction. To build an intelligent and automatic physical education teaching mode, this paper combines human-computer interaction based on speech recognition technology with physical education teaching. Students input through voice signals, and the system receives signals, analyzes signals, recognizes signals, and feeds back information to students in multiple forms. For the system to process the external speech signal, this paper uses the Mel cepstral coefficient algorithm to extract the speech information. By comparing the speech recognition rate and antinoise rate of Hidden Markov Model, Probabilistic Statistics Neural Network, and Hybrid Model (Hidden Markov and Rate Statistical Neural Network combination), the speech recognition engine uses the hybrid model, and its speech recognition rate is 98.3%, and the average antinoise rate can reach 85%. By comparing the human-computer interaction physical education teaching method with the traditional teaching method, the human-computer interaction method is superior to the traditional teaching method in the acquisition of physical knowledge, the acquisition of physical skills, the satisfaction of physical education courses and the ability of active learning. It effectively solves the drawbacks of traditional physical education and rationally uses human-computer interaction technology. On the basis of not violating physical education, realize the diversification of physical education, improve the quality of teaching, improve students' individual development and students' autonomous learning ability. Therefore, the combination of human-computer interaction and physical education based on recognition engine technology is the trend of today's physical education development. |
format | Online Article Text |
id | pubmed-9339716 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-93397162022-08-02 Human-computer interactive physical education teaching method based on speech recognition engine technology Sang, Yunpeng Chen, Xingquan Front Public Health Public Health With the advent of the era of artificial intelligence, speech recognition engine technology has a profound impact on social production, life, education, and other fields. Voice interaction is the most basic and practical type of human-computer interaction. To build an intelligent and automatic physical education teaching mode, this paper combines human-computer interaction based on speech recognition technology with physical education teaching. Students input through voice signals, and the system receives signals, analyzes signals, recognizes signals, and feeds back information to students in multiple forms. For the system to process the external speech signal, this paper uses the Mel cepstral coefficient algorithm to extract the speech information. By comparing the speech recognition rate and antinoise rate of Hidden Markov Model, Probabilistic Statistics Neural Network, and Hybrid Model (Hidden Markov and Rate Statistical Neural Network combination), the speech recognition engine uses the hybrid model, and its speech recognition rate is 98.3%, and the average antinoise rate can reach 85%. By comparing the human-computer interaction physical education teaching method with the traditional teaching method, the human-computer interaction method is superior to the traditional teaching method in the acquisition of physical knowledge, the acquisition of physical skills, the satisfaction of physical education courses and the ability of active learning. It effectively solves the drawbacks of traditional physical education and rationally uses human-computer interaction technology. On the basis of not violating physical education, realize the diversification of physical education, improve the quality of teaching, improve students' individual development and students' autonomous learning ability. Therefore, the combination of human-computer interaction and physical education based on recognition engine technology is the trend of today's physical education development. Frontiers Media S.A. 2022-07-18 /pmc/articles/PMC9339716/ /pubmed/35923977 http://dx.doi.org/10.3389/fpubh.2022.941083 Text en Copyright © 2022 Sang and Chen. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Public Health Sang, Yunpeng Chen, Xingquan Human-computer interactive physical education teaching method based on speech recognition engine technology |
title | Human-computer interactive physical education teaching method based on speech recognition engine technology |
title_full | Human-computer interactive physical education teaching method based on speech recognition engine technology |
title_fullStr | Human-computer interactive physical education teaching method based on speech recognition engine technology |
title_full_unstemmed | Human-computer interactive physical education teaching method based on speech recognition engine technology |
title_short | Human-computer interactive physical education teaching method based on speech recognition engine technology |
title_sort | human-computer interactive physical education teaching method based on speech recognition engine technology |
topic | Public Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9339716/ https://www.ncbi.nlm.nih.gov/pubmed/35923977 http://dx.doi.org/10.3389/fpubh.2022.941083 |
work_keys_str_mv | AT sangyunpeng humancomputerinteractivephysicaleducationteachingmethodbasedonspeechrecognitionenginetechnology AT chenxingquan humancomputerinteractivephysicaleducationteachingmethodbasedonspeechrecognitionenginetechnology |