Title: Multi-note intelligent fusion method of music based on artificial neural network

Authors: Ye Tian

Addresses: School of Music and Dance, Mudanjiang Normal University, Mudanjiang 157011, China

Abstract: In order to overcome the problems of low fusion efficiency and poor fusion quality of the traditional music multi-note fusion method, an intelligent fusion method of music multi-note based on artificial neural network is proposed. Establish a multi-note model, and analyse the basic signal structure of notes under this model. Collect the initial music audio file, and preprocess the audio file through the steps of parsing, noise reduction, filtering and calibration. Use artificial neural network to segment unit music, extract fundamental note, peak note and melody note, and output in the form of a single note. Extract the features of different notes, and realise the intelligent fusion of music multi-notes according to the feature extraction results. The experimental results show that, compared with the traditional fusion method, the fusion speed of the designed intelligent fusion method is increased by at least 12.6s, and the signal-to-noise ratio is increased by 1.23.

Keywords: artificial neural network; music processing; multi-note fusion; contour curve.

DOI: 10.1504/IJART.2021.115763

International Journal of Arts and Technology, 2021 Vol.13 No.1, pp.1 - 17

Received: 24 Apr 2020
Accepted: 03 Sep 2020
Published online: 21 Jun 2021 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article