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<p>In this paper, firstly, under the perspective of big data, the innovation research of piano intelligent teaching mode and the application strategy of intelligent piano teaching mode under big data thinking are explained, respectively. Secondly, in music recognition in a college piano classroom, the piano music signal needs to be sampled, quantized and pre-processed to avoid the frequency bias caused by the low-frequency components of the piano music signal. Then, based on the big data technology, the piano intelligent teaching note recognition system is constructed by using the improved time domain algorithm and the improved time-frequency domain combination algorithm, and the recognition of note time value in piano intelligent teaching and the piano intelligent teaching note recognition system are studied and analyzed. The results show that the improved time-frequency domain combination is more effective in responding to the time-value information of piano music signals in recognition simulation. The note recognition system studied in this project has seen a recognition rate increase of almost 5% in system performance. This paper studies the application of intelligent piano teaching in professional learning in universities, which can lead to the development and popularity of intelligent teaching methods in piano classrooms.</p>
</abstract>

In this paper, firstly, under the perspective of big data, the innovation research of piano intelligent teaching mode and the application strategy of intelligent piano teaching mode under big data thinking are explained, respectively. Secondly, in music recognition in a college piano classroom, the piano music signal needs to be sampled, quantized and pre-processed to avoid the frequency bias caused by the low-frequency components of the piano music signal. Then, based on the big data technology, the piano intelligent teaching note recognition system is constructed by using the improved time domain algorithm and the improved time-frequency domain combination algorithm, and the recognition of note time value in piano intelligent teaching and the piano intelligent teaching note recognition system are studied and analyzed. The results show that the improved time-frequency domain combination is more effective in responding to the time-value information of piano music signals in recognition simulation. The note recognition system studied in this project has seen a recognition rate increase of almost 5% in system performance. This paper studies the application of intelligent piano teaching in professional learning in universities, which can lead to the development and popularity of intelligent teaching methods in piano classrooms.

Research on the intelligent teaching mode of college piano classroom based on big data technology

Guangdong University of Foreign Studies South China Business College

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

In this paper, firstly, under the perspective of big data, the innovation research of piano intelligent teaching mode and the application strategy of...

Research on the intelligent teaching mode of college piano classroom based on big data technology

Online veröffentlicht: 30. Okt. 2023

Seitenbereich: -

Eingereicht: 11. Nov. 2022

Akzeptiert: 10. Mai 2023

DOI: https://doi.org/10.2478/amns.2023.2.00889

Schlüsselwörter
Time-domain algorithm, Time-frequency domain combined algorithm, Piano intelligent teaching, Note recognition system, Note time value

© 2023 Yanhong Huang, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Research on the intelligent teaching mode of college piano classroom based on big data technology

Online veröffentlicht: 30. Okt. 2023

Seitenbereich: -

Eingereicht: 11. Nov. 2022

Akzeptiert: 10. Mai 2023

DOI: https://doi.org/10.2478/amns.2023.2.00889

SchlüsselwörterTime-domain algorithm, Time-frequency domain combined algorithm, Piano intelligent teaching, Note recognition system, Note time value

© 2023 Yanhong Huang, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Time-domain algorithm, Time-frequency domain combined algorithm, Piano intelligent teaching, Note recognition system, Note time value