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Research on the Application of BP Neural Network in Vocal Music Teaching Quality Evaluation

机译：BP神经网络在声乐教学质量评估中的应用研究

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摘要

To solve the problem that the evaluation of vocal music teaching is influenced by multiple factors and subjective factors in scoring, BP neural network is proposed to simulate the nonlinear mapping of various factors and establish the vocal music evaluation system. At the same time, aiming at the disadvantage of slow training speed of BP network, a momentum model with adjustment coefficient is put forward, and a new weight adjustment formula is given. The idea of the algorithm and the optimization measures it takes are summarized, the establishment of improved algorithm model is completed, and the steps of network training algorithm are realized. Finally, taking the vocal music evaluation system as the input, BP neural network is used to establish the teaching quality evaluation model. The simulation results show that the improved scheme has the characteristics of fast convergence, strong optimization ability and generalization ability, which effectively weakens the influence of human factors in the determination of index weight.
机译：为解决声乐教学评价在评分中受多个因素和主观因素影响的问题，提出了BP神经网络对各种因素的非线性映射进行仿真，建立声乐评价体系。同时针对BP网络训练速度慢的缺点，提出了具有调整系数的动量模型，并给出了新的权重调整公式。总结了算法的思想和优化措施，完成了改进算法模型的建立，实现了网络训练算法的步骤。最后，以声乐评价系统为输入，采用BP神经网络建立教学质量评价模型。仿真结果表明，改进方案具有收敛速度快，优化能力强，泛化能力强的特点，有效地减弱了人为因素对指标权重确定的影响。

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