# SoundSpaces 2.0: A Simulation Platform for Visual-Acoustic Learning

arXiv: https://arxiv.org/abs/2206.08312 · HTML: https://mlsanity.com/paper/2206.08312/

## Key facts

- Cited by 95 papers in the map (data through 14 Oct 2026).
- Builds on 49 of its 99 references that are in the map.
- First posted on arXiv 16 Jun 2022.

## Builds on (most cited first, 30 of 49)

- [Ego4D: Around the World in 3,000 Hours of Egocentric Video](https://mlsanity.com/paper/2110.07058/) (2021)
- [Domain Randomization for Transferring Deep Neural Networks from Simulation to the Real World](https://mlsanity.com/paper/1703.06907/) (2017)
- [Matterport3D: Learning from RGB-D Data in Indoor Environments](https://mlsanity.com/paper/1709.06158/) (2017)
- [Habitat: A Platform for Embodied AI Research](https://mlsanity.com/paper/1904.01201/) (2019)
- [A Comprehensive Survey on Transfer Learning](https://mlsanity.com/paper/1911.02685/) (2019)
- [Vision-and-Language Navigation: Interpreting visually-grounded navigation instructions in real environments](https://mlsanity.com/paper/1711.07280/) (2017)
- [The Replica Dataset: A Digital Replica of Indoor Spaces](https://mlsanity.com/paper/1906.05797/) (2019)
- [AI2-THOR: An Interactive 3D Environment for Visual AI](https://mlsanity.com/paper/1712.05474/) (2017)
- [Habitat-Matterport 3D Dataset (HM3D): 1000 Large-scale 3D Environments for Embodied AI](https://mlsanity.com/paper/2109.08238/) (2021)
- [Habitat 2.0: Training Home Assistants to Rearrange their Habitat](https://mlsanity.com/paper/2106.14405/) (2021)
- [Gibson Env: Real-World Perception for Embodied Agents](https://mlsanity.com/paper/1808.10654/) (2018)
- [Sim-to-Real Transfer in Deep Reinforcement Learning for Robotics: a Survey](https://mlsanity.com/paper/2009.13303/) (2020)
- [SpeechBrain: A General-Purpose Speech Toolkit](https://mlsanity.com/paper/2106.04624/) (2021)
- [DD-PPO: Learning Near-Perfect PointGoal Navigators from 2.5 Billion Frames](https://mlsanity.com/paper/1911.00357/) (2019)
- [Audio-Visual Scene Analysis with Self-Supervised Multisensory Features](https://mlsanity.com/paper/1804.03641/) (2018)
- [Self-Supervised Learning by Cross-Modal Audio-Video Clustering](https://mlsanity.com/paper/1911.12667/) (2019)
- [ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation](https://mlsanity.com/paper/2007.04954/) (2020)
- [Cooperative Learning of Audio and Video Models from Self-Supervised Synchronization](https://mlsanity.com/paper/1807.00230/) (2018)
- [The Sound of Motions](https://mlsanity.com/paper/1904.05979/) (2019)
- [Pyroomacoustics: A Python package for audio room simulations and array processing algorithms](https://mlsanity.com/paper/1710.04196/) (2017)
- [Habitat-Web: Learning Embodied Object-Search Strategies from Human Demonstrations at Scale](https://mlsanity.com/paper/2204.03514/) (2022)
- [The Conversation: Deep Audio-Visual Speech Enhancement](https://mlsanity.com/paper/1804.04121/) (2018)
- [Discriminative Sounding Objects Localization via Self-supervised Audiovisual Matching](https://mlsanity.com/paper/2010.05466/) (2020)
- [Look, Listen, and Act: Towards Audio-Visual Embodied Navigation](https://mlsanity.com/paper/1912.11684/) (2019)
- [Learning Representations from Audio-Visual Spatial Alignment](https://mlsanity.com/paper/2011.01819/) (2020)
- [EnvEdit: Environment Editing for Vision-and-Language Navigation](https://mlsanity.com/paper/2203.15685/) (2022)
- [Semantic Audio-Visual Navigation](https://mlsanity.com/paper/2012.11583/) (2020)
- [An Overview of Deep-Learning-Based Audio-Visual Speech Enhancement and Separation](https://mlsanity.com/paper/2008.09586/) (2020)
- [ObjectFolder 2.0: A Multisensory Object Dataset for Sim2Real Transfer](https://mlsanity.com/paper/2204.02389/) (2022)
- [Learning Neural Acoustic Fields](https://mlsanity.com/paper/2204.00628/) (2022)

## Built on by (most cited first, 30 of 95)

- [Evaluating Real-World Robot Manipulation Policies in Simulation](https://mlsanity.com/paper/2405.05941/) (2024)
- [ARNOLD: A Benchmark for Language-Grounded Task Learning With Continuous States in Realistic 3D Scenes](https://mlsanity.com/paper/2304.04321/) (2023)
- [Audio-Visual Grouping Network for Sound Localization from Mixtures](https://mlsanity.com/paper/2303.17056/) (2023)
- [AV-NeRF: Learning Neural Fields for Real-World Audio-Visual Scene Synthesis](https://mlsanity.com/paper/2302.02088/) (2023)
- [SPOC: Imitating Shortest Paths in Simulation Enables Effective Navigation and Manipulation in the Real World](https://mlsanity.com/paper/2312.02976/) (2023)
- [Retrospectives on the Embodied AI Workshop](https://mlsanity.com/paper/2210.06849/) (2022)
- [STARSS23: An Audio-Visual Dataset of Spatial Recordings of Real Scenes with Spatiotemporal Annotations of Sound Events](https://mlsanity.com/paper/2306.09126/) (2023)
- [MultiPLY: A Multisensory Object-Centric Embodied Large Language Model in 3D World](https://mlsanity.com/paper/2401.08577/) (2024)
- [BAT: Learning to Reason about Spatial Sounds with Large Language Models](https://mlsanity.com/paper/2402.01591/) (2024)
- [Novel-View Acoustic Synthesis](https://mlsanity.com/paper/2301.08730/) (2023)
- [SepPrune: Structured Pruning for Efficient Deep Speech Separation](https://mlsanity.com/paper/2505.12079/) (2025)
- [EgoChoir: Capturing 3D Human-Object Interaction Regions from Egocentric Views](https://mlsanity.com/paper/2405.13659/) (2024)
- [Unveiling the Power of Audio-Visual Early Fusion Transformers with Dense Interactions through Masked Modeling](https://mlsanity.com/paper/2312.01017/) (2023)
- [A Unified Audio-Visual Learning Framework for Localization, Separation, and Recognition](https://mlsanity.com/paper/2305.19458/) (2023)
- [Action2Sound: Ambient-Aware Generation of Action Sounds from Egocentric Videos](https://mlsanity.com/paper/2406.09272/) (2024)
- [AV-RIR: Audio-Visual Room Impulse Response Estimation](https://mlsanity.com/paper/2312.00834/) (2023)
- [Real Acoustic Fields: An Audio-Visual Room Acoustics Dataset and Benchmark](https://mlsanity.com/paper/2403.18821/) (2024)
- [Omnidirectional Information Gathering for Knowledge Transfer-based Audio-Visual Navigation](https://mlsanity.com/paper/2308.10306/) (2023)
- [Pay Self-Attention to Audio-Visual Navigation](https://mlsanity.com/paper/2210.01353/) (2022)
- [Sound Localization from Motion: Jointly Learning Sound Direction and Camera Rotation](https://mlsanity.com/paper/2303.11329/) (2023)
- [ReALFRED: An Embodied Instruction Following Benchmark in Photo-Realistic Environments](https://mlsanity.com/paper/2407.18550/) (2024)
- [AdVerb: Visually Guided Audio Dereverberation](https://mlsanity.com/paper/2308.12370/) (2023)
- [Audio-Guided Dynamic Modality Fusion with Stereo-Aware Attention for Audio-Visual Navigation](https://mlsanity.com/paper/2509.16924/) (2025)
- [Self-Supervised Visual Acoustic Matching](https://mlsanity.com/paper/2307.15064/) (2023)
- [Advancing Audio-Visual Navigation Through Multi-Agent Collaboration in 3D Environments](https://mlsanity.com/paper/2509.22698/) (2025)
- [Iterative Residual Cross-Attention Mechanism: An Integrated Approach for Audio-Visual Navigation Tasks](https://mlsanity.com/paper/2509.25652/) (2025)
- [Exploring Embodied Multimodal Large Models: Development, Datasets, and Future Directions](https://mlsanity.com/paper/2502.15336/) (2025)
- [Dynamic Multi-Target Fusion for Efficient Audio-Visual Navigation](https://mlsanity.com/paper/2509.21377/) (2025)
- [Hearing Anything Anywhere](https://mlsanity.com/paper/2406.07532/) (2024)
- [Modeling and Driving Human Body Soundfields through Acoustic Primitives](https://mlsanity.com/paper/2407.13083/) (2024)

## Abstract (arXiv)

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.