julian-parker/DAFX22_FNO
Code associated with the paper "Physical Modeling using Recurrent Neural Networks with Fast Convolutional Layers"
This project helps audio engineers and researchers working with sound to create digital models of acoustic, mechanical, and electrical systems. You provide data from a real or simulated physical system, and it generates a neural network model that can mimic its sound behavior. This is ideal for those developing new digital musical instruments or sound effects.
No commits in the last 6 months.
Use this if you need to build accurate, data-driven digital emulations of physical sound-producing systems, especially those with complex spatial characteristics.
Not ideal if you're looking for pre-built sound effects or require traditional mathematical modeling approaches rather than data-driven machine learning.
Stars
21
Forks
3
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Dec 18, 2023
Commits (30d)
0
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