89 citations · 231 across the 12 of their papers we have counts for
5 papers · 1 filter
Learning audio representations via phase prediction
Félix de Chaumont Quitry, Marco Tagliasacchi, Dominik Roblek
We learn audio representations by solving a novel self-supervised learning task, which consists of predicting the phase of the short-time Fourier transform from its magnitude. A co…
SPICE: Self-supervised Pitch Estimation
Beat Gfeller, Christian Frank, Dominik Roblek +3
We propose a model to estimate the fundamental frequency in monophonic audio, often referred to as pitch estimation. We acknowledge the fact that obtaining ground truth annotations…
From Here to There: Video Inbetweening Using Direct 3D Convolutions
Yunpeng Li, Dominik Roblek, Marco Tagliasacchi
We consider the problem of generating plausible and diverse video sequences, when we are only given a start and an end frame. This task is also known as inbetweening, and it belong…
Self-supervised audio representation learning for mobile devices
Marco Tagliasacchi, Beat Gfeller, Félix de Chaumont Quitry +1
We explore self-supervised models that can be potentially deployed on mobile devices to learn general purpose audio representations. Specifically, we propose methods that exploit t…
Fréchet Audio Distance: A Metric for Evaluating Music Enhancement Algorithms
Kevin Kilgour, Mauricio Zuluaga, Dominik Roblek +1
We propose the Fréchet Audio Distance (FAD), a novel, reference-free evaluation metric for music enhancement algorithms. We demonstrate how typical evaluation metrics for speech en…