Music intelligent recognition system based on Leap motion sensor
In today's continuous development of intelligent technology,music intelligent recognition system has become an im-portant bridge connecting technology and art.Especially in the field of piano teaching,the application of intelligent recognition tech-nology is particularly important due to its learning difficulty and high education cost.To this end,the research is dedicated to the de-velopment of a Leap Motion sensor-based music intelligent recognition system,which aims to provide a more efficient and intuitive learning method for piano beginners by recognising and analysing the gestural movements of piano experts.The study combines the physiological structure and playing characteristics of fingers,establishes a kinematic model of finger keystroke incorporating Denavit-Hartenberg parameters,and uses the data captured by Leap Motion to evaluate finger playing via inverse neural network.The results showed that finger playing velocity features were successfully captured;the data were processed by a specific denoising algorithm with 98％accuracy.And the error of the neural network on the test sample is only 0.34％,showing the high accuracy of the model.This study brings important insights to the field of music intelligent recognition.
万方数据
维普
