3 citations · 3 across the 5 of their papers we have counts for
4 papers
Extreme Audio Time Stretching Using Neural Synthesis
Leonardo Fierro, Alec Wright, Vesa Välimäki +1
A deep neural network solution for time-scale modification (TSM) focused on large stretching factors is proposed, targeting environmental sounds. Traditional TSM artifacts such as…
A Two-Stage U-Net for High-Fidelity Denoising of Historical Recordings
Eloi Moliner, Vesa Välimäki
Enhancing the sound quality of historical music recordings is a long-standing problem. This paper presents a novel denoising method based on a fully-convolutional deep neural netwo…
Perceptual Loss Function for Neural Modelling of Audio Systems
Alec Wright, Vesa Välimäki
This work investigates alternate pre-emphasis filters used as part of the loss function during neural network training for nonlinear audio processing. In our previous work, the err…
Deep Learning for Tube Amplifier Emulation
Eero-Pekka Damskägg, Lauri Juvela, Etienne Thuillier +1
Analog audio effects and synthesizers often owe their distinct sound to circuit nonlinearities. Faithfully modeling such significant aspect of the original sound in virtual analog…