Back to Search Start Over

Construction and Research of Guqin Sound Synthesis and Plucking Big Data Simulation Model Based on Computer Synthesis Technology

Authors :
MingQing Liu
Source :
Discrete Dynamics in Nature and Society, Vol 2022 (2022)
Publication Year :
2022
Publisher :
Hindawi Limited, 2022.

Abstract

The application and economic efficiency evaluation mode of traditional composition in the field of modern music cannot meet the needs of various types of music in China, especially Guqin music. Based on this, this paper studies the big data simulation model of Guqin sound synthesis and plucking based on computer composition technology. The computer composition technology uses the discrete dynamic modeling technology of complex system to complete the computer simulation of Guqin sound through the analysis of the correlation between Guqin music data and realizes the storage and analysis of the generated Guqin sound data. In addition, the technology can analyze the data information of composition mode in the piano sound plucking simulation model with the classical Guqin music data stored in the cloud system over the years and then feed it back to relevant professionals for verification. The experimental results show that the Guqin sound simulation model can efficiently compare and analyze the melody and other data of classical Guqin sound with the simulated Guqin sound and can realize secondary data mining. This paper studies the application of computer composition method based on discrete dynamic modeling technology in Guqin sound simulation, which has certain reference significance for improving the cloud data in China’s modern music field and the intelligent construction of Guqin sound data cloud storage system.

Subjects

Subjects :
Mathematics
QA1-939

Details

Language :
English
ISSN :
1607887X
Volume :
2022
Database :
Directory of Open Access Journals
Journal :
Discrete Dynamics in Nature and Society
Publication Type :
Academic Journal
Accession number :
edsdoj.2c647c7f572c41a59408997158dbafae
Document Type :
article
Full Text :
https://doi.org/10.1155/2022/1516648