AI music teaching innovation research based on artificial intelligence technology

With the rapid development of artificial intelligence technology, the application of AI technology in the field of music teaching has attracted more and more attention, but there is a problem that innovation and optimization are not ideal. The traditional music teaching mode cannot solve the problem of innovation and optimization in the field of music education, and the evaluation is unreasonable. Therefore, this paper proposes a neural network algorithm for innovative optimization teaching innovation analysis. Firstly, based on pedagogical theory, the existing AI music teaching methods are analyzed in order to scientifically classify the teaching quality evaluation requirements, so as to reduce the undesirable factors in teaching innovation. Secondly, pedagogical theory can be used to evaluate the quality of AI music teaching, formulate corresponding teaching quality evaluation schemes, and comprehensively analyze the results of innovative practices in teaching. The results show that under the same evaluation criteria, the neural network algorithm is superior to the traditional music teaching mode in terms of quality evaluation accuracy and innovative effect of AI music teaching.