2022
DOI: 10.1155/2022/3928889
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Analysis of Music Teaching in Basic Education Integrating Scientific Computing Visualization and Computer Music Technology

Abstract: In the current music education, the music teaching method is too simple, boring, relatively backward, unable to attract the attention of the students, and the students gradually lose their interest in music courses. In basic education, music, as a highly practical subject, must create a good classroom atmosphere, make the classroom active, and enable students to better experience music, enjoy music, and like music. Therefore, in order to change this situation, this paper, based on scientific computing visualiz… Show more

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Cited by 4 publications
(2 citation statements)
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“…The systems can then create novel, original music that complies with these learnt styles. Researchers (Zhao, 2022;Shang & Shao, 2022;Xu, 2020) are conducting investigations on how AI and machine learning can offer novel insights into the biology and neuroscience of music and hearing, without subjective evaluations. There is an emphasis on ensuring that technical terms are explained upon first use and that there is a clear, objective flow of information with causal connections between statements.…”
Section: Sayfa 755mentioning
confidence: 99%
“…The systems can then create novel, original music that complies with these learnt styles. Researchers (Zhao, 2022;Shang & Shao, 2022;Xu, 2020) are conducting investigations on how AI and machine learning can offer novel insights into the biology and neuroscience of music and hearing, without subjective evaluations. There is an emphasis on ensuring that technical terms are explained upon first use and that there is a clear, objective flow of information with causal connections between statements.…”
Section: Sayfa 755mentioning
confidence: 99%
“…Two essential pieces of technological equipment for the cepstral area assessment are the Mel frequency cepstral factor and the straight predictive cepstral factor. Simultaneously, the music education curriculum is heavily influenced by noise and leads to the existing audio classifiers implementation that fall short of potential needs [13][14][15]. Most of the common methods of research depend on traditional signal processing techniques and a less study on music appreciation utilizing deep neural networks and much growth potential in the appreciation precision along productivity [16].…”
Section: Introductionmentioning
confidence: 99%