A Piano Single Tone Recognition and Classification Method Based on CNN Model

Abstract

In order to improve the recognition and classification effect of piano single tone, this paper combines the CNN (Convolutional Neural Networks) model to construct the piano single tone recognition and classification model, and equalizes the uniformly irradiated parabolic tone transmission hardware. In this paper, the analytic method is used to calculate the direction diagram of the tone transmission hardware, and the analytical expression for calculating the gain of the tone transmission hardware is obtained. Moreover, this paper gives the calculation and analytical expression of the hardware gain of the tone transmission in the main lobe, and obtains the calculation method of the relative position of the two tone transmission hardware by using the conversion relationship between the global coordinate and the local coordinate. Finally, the variation law of the received power with the azimuth/elevation angle of the receiving tone transmission hardware and the incident high-power microwave frequency is given. The experimental study shows that the piano single tone recognition and classification method based on CNN model proposed in this paper can play an important role in piano single tone recognition. This article improves the note recognition algorithm for piano music by combining note features with frequency spectrum to obtain note spectrum, which improves the accuracy of audio classification recognition.