Design of real-time rhythm tracking system based on neural network

In order to solve the problems of real-time beat tracking, such as the uncertainty of real beat value, the difficulty of getting close to people’s perception of music and the position of beat according to people’s feelings, the fact that most data sets are private and the amount of data is small, which affects the accuracy of experimental results, a real-time beat tracking method based on lstm neural network is proposed, which abandons the traditional idea of beat tracking to determine the position of beat, divides the beat into five levels according to the degree of strength, and then trains the beat information by using lstm network. Experiments show that the system functions well and the accuracy of the training results is guaranteed to reach 0.946.