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Vocal Intelligence Training System for Music Performance Majors based on Multi-point Signal Recognition and Fusion

Vocal intelligence training system for the music performance majors based on multi-point signal recognition and fusion is studied in the paper. In the process of signal acquisition, whether it is MIDI signal acquisition or audio signal acquisition, there is a certain delay. The delay of the recording equipment, the slow signal processing speed and the lag of the software feedback all bring a lot of core inconvenience to the software implementation process. Hence, to face this challenge, a novel multi-point signal recognition and fusion model has been designed. The recognition algorithm combines the core advantages of both supervised learning and unsupervised learning, and can use a small amount of labeled sample data and a large amount of unlabeled sample data for identification. Furthermore, the vocal information is selected to be tested. Through the comparison testing, the accuracy of the designed model is reflected to be 95.98% which is much higher than the traditional ones.