Open AccessGENERATION OF PERCUSSION INSTRUMENT PARTS USING A NEURAL NETWORK
Author(s) -
I. V. Fedotova,
M. K. O. Manafov
Publication year - 2020
Publication title -
prikladnaâ matematika i fundamentalʹnaâ informatika
Language(s) - English
Resource type - Journals
ISSN - 2311-4908
DOI - 10.25206/2311-4908-2020-7-3-29-37
Subject(s) - percussion , artificial neural network , computer science , automation , drum , process (computing) , virtual instrument , quality (philosophy) , rhythm , artificial intelligence , engineering , mechanical engineering , acoustics , software , operating system , philosophy , physics , epistemology
This article discusses the automation of the process of creating batches of percussion instruments using a neural network. The LSTM neural network for generating drum parts is considered as a tool. The results of the conducted studies allow us to conclude that despite the ability of the LSTM neural network to generate percussion instrument parts with a stable rhythm, the quality of the generated parts is inferior to the quality of human-made parts.