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We introduce SoundSpaces 2.0, a platform for on-the-fly geometry-based audiorendering for 3D environments. Given a 3D mesh of a real-world environment,SoundSpaces can generate highly realistic acoustics for arbitrary soundscaptured from arbitrary microphone locations. Together with existing 3D visualassets, it supports an array of audio-visual research tasks, such asaudio-visual navigation, mapping, source localization and separation, andacoustic matching. Compared to existing resources, SoundSpaces 2.0 has theadvantages of allowing continuous spatial sampling, generalization to novelenvironments, and configurable microphone and material properties. To ourknowledge, this is the first geometry-based acoustic simulation that offershigh fidelity and realism while also being fast enough to use for embodiedlearning. We showcase the simulator's properties and benchmark its performanceagainst real-world audio measurements. In addition, we demonstrate twodownstream tasks -- embodied navigation and far-field automatic speechrecognition -- and highlight sim2real performance for the latter. SoundSpaces2.0 is publicly available to facilitate wider research for perceptual systemsthat can both see and hear.

SoundSpaces 2.0: A Simulation Platform for Visual-Acoustic Learning