View the Project on GitHub mchijmma/modeling-plate-spring-reverb
Audio examples for the paper:
Martínez Ramírez M. A., Benetos, E. and Reiss J. D., “Modeling plate and spring reverberation using a DSP-informed deep neural network” in the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Barcelona, Spain, May 2020.
Block diagram of the proposed model; adaptive front-end, latent-space and synthesis back-end:
Detailed architecture of adaptive front-end:
Input frame size of 4096 samples and ±4 context frames.
Block diagram of the latent-space:
Detailed architecture of the latent-space:
Block diagram of the synthesis back-end:
Detailed architecture of the synthesis back-end:
Output frame size of 4096 samples.
Plate and Spring settings:
@inproceedings{martinez2020modeling,
title={Modeling plate and spring reverberation using a {DSP}-informed deep neural network},
author={Mart'{i}nez Ram'{i}rez, Marco A and Benetos, Emmanouil and Reiss, Joshua D},
booktitle={IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
month = {May},
year = {2020},
location = {Barcelona, Spain}
}