The research has organically integrated VR and multimedia technology, built a corresponding piano teaching platform, and verified its effectiveness through experiments. The experimental results show that the classification effect, classification accuracy and recognition rate have been significantly enhanced after the internal selection algorithm of VR-MM is improved. Among them, the VLRAMM-BPNN algorithm, combining the two improved algorithms with BPNN, has the best performance, the highest coincidence between actual and predicted classification results, the highest classification accuracy of 95.93%, and the recognition rate is 21.6% higher than that of BPNN. According to the overall performance test of VR-MM, both the response speed and various stress tests have achieved the desired results. When the number of people is set at 10,000, the pressure has also reached the bottleneck, fully meeting the actual needs of piano teaching. To sum up, the performance of VR-MM has achieved the expected effect.
No takes yet. Share an insight, caveat, or question.
Peng Liu (2023) studied this question.
Synapse has enriched 5 related papers. Consider them for comparative context: