  We introduce SoundSpaces 2.0, a platform for on-the-fly geometry-based audio
rendering for 3D environments. Given a 3D mesh of a real-world environment,
SoundSpaces can generate highly realistic acoustics for arbitrary sounds
captured from arbitrary microphone locations. Together with existing 3D visual
assets, it supports an array of audio-visual research tasks, such as
audio-visual navigation, mapping, source localization and separation, and
acoustic matching. Compared to existing resources, SoundSpaces 2.0 has the
advantages of allowing continuous spatial sampling, generalization to novel
environments, and configurable microphone and material properties. To our
knowledge, this is the first geometry-based acoustic simulation that offers
high fidelity and realism while also being fast enough to use for embodied
learning. We showcase the simulator's properties and benchmark its performance
against real-world audio measurements. In addition, we demonstrate two
downstream tasks -- embodied navigation and far-field automatic speech
recognition -- and highlight sim2real performance for the latter. SoundSpaces
2.0 is publicly available to facilitate wider research for perceptual systems
that can both see and hear.
