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深度学习双重神经网络在钢琴教育在线课程学习模型构建中的应用。

Deep Learning Dual Neural Networks in the Construction of Learning Models for Online Courses in Piano Education.

机构信息

Guangzhou College of Technology and Business, Guangzhou, Guangdong 510000, China.

College of Music and Dance, Guangzhou University, Guangzhou, Guangdong 510000, China.

出版信息

Comput Intell Neurosci. 2022 Jul 13;2022:4408288. doi: 10.1155/2022/4408288. eCollection 2022.

Abstract

The use of deep learning (DL) and artificial intelligence (AI) in teaching children piano lessons promotes modern piano instruction and enhances the overall quality of education. To begin, a more thorough explanation of the teaching environment and the intelligent piano's features is provided. Then, a method for detecting the onset of a piano note using a Dual Neural Network (DNN) is proposed. By transforming the original time-domain waveform of the piano music signal into a frequency distribution that changes with time, the network can analyze the input signal's time-frequency. Finally, the intelligent piano teaching method combines deep learning with artificial intelligence (AI) to produce the best possible results for students learning the piano instrument. For children and their parents alike, it is a favorite, and it significantly impacts their interests. The proposed model has a 94% overall accuracy rate.

摘要

深度学习(DL)和人工智能(AI)在儿童钢琴教学中的应用促进了现代钢琴教学,并提高了整体教育质量。首先,提供了更详细的教学环境和智能钢琴的功能说明。然后,提出了一种使用双神经网络(DNN)检测钢琴音符起始的方法。通过将钢琴音乐信号的原始时域波形转换为随时间变化的频率分布,该网络可以分析输入信号的时频。最后,智能钢琴教学方法将深度学习与人工智能(AI)相结合,为学习钢琴乐器的学生取得最佳效果。对于孩子和他们的父母来说,这是一个最爱,它极大地影响了他们的兴趣。所提出的模型具有 94%的整体准确率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d34/9300362/8422a793eed1/CIN2022-4408288.001.jpg

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