4 citations · 8 across the 5 of their papers we have counts for
5 papers
Sample-Efficient Preference-based Reinforcement Learning with Dynamics Aware Rewards
Katherine Metcalf, Miguel Sarabia, Natalie Mackraz +1
Preference-based reinforcement learning (PbRL) aligns a robot behavior with human preferences via a reward function learned from binary feedback over agent behaviors. We show that…
Spatial LibriSpeech: An Augmented Dataset for Spatial Audio Learning
Miguel Sarabia, Elena Menyaylenko, Alessandro Toso +7
We present Spatial LibriSpeech, a spatial audio dataset with over 650 hours of 19-channel audio, first-order ambisonics, and optional distractor noise. Spatial LibriSpeech is desig…
Rewards Encoding Environment Dynamics Improves Preference-based Reinforcement Learning
Katherine Metcalf, Miguel Sarabia, Barry-John Theobald
Preference-based reinforcement learning (RL) algorithms help avoid the pitfalls of hand-crafted reward functions by distilling them from human preference feedback, but they remain…
Contrastive Self-Supervised Learning for Skeleton Representations
Nico Lingg, Miguel Sarabia, Luca Zappella +1
Human skeleton point clouds are commonly used to automatically classify and predict the behaviour of others. In this paper, we use a contrastive self-supervised learning method, Si…
On the role of Lip Articulation in Visual Speech Perception
Zakaria Aldeneh, Masha Fedzechkina, Skyler Seto +4
Generating realistic lip motion from audio to simulate speech production is critical for driving natural character animation. Previous research has shown that traditional metrics u…