mlsanityData to 7 Oct 2026

Direction-Aware Neural Acoustic Fields for Few-Shot Interpolation of Ambisonic Impulse Responses

arXiv 2505.13617 ↗First posted 19 May 2025eess.AS cs.AI cs.CVcited by 1

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Abstract (arXiv)

The characteristics of a sound field are intrinsically linked to the geometric and spatial properties of the environment surrounding a sound source and a listener. The physics of sound propagation is captured in a time-domain signal known as a room impulse response (RIR). Prior work using neural fields (NFs) has allowed learning spatially-continuous representations of RIRs from finite RIR measurements. However, previous NF-based methods have focused on monaural omnidirectional or at most binaural listeners, which does not precisely capture the directional characteristics of a real sound field at a single point. We propose a direction-aware neural field (DANF) that more explicitly incorporates the directional information by Ambisonic-format RIRs. While DANF inherently captures spatial relations between sources and listeners, we further propose a direction-aware loss. In addition, we investigate the ability of DANF to adapt to new rooms in various ways including low-rank adaptation.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 11 of its 29 references that are in the map. First posted on arXiv 19 May 2025.

Builds on

11 of 29 references.

References · 11

  1. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,084
  2. 2017Matterport3D: Learning from RGB-D Data in Indoor Environmentscited by 1,354
  3. 2017Pyroomacoustics: A Python package for audio room simulations and array processing algorithmscited by 131
  4. 2022SoundSpaces 2.0: A Simulation Platform for Visual-Acoustic Learningcited by 93
  5. 2022Learning Neural Acoustic Fieldscited by 65
  6. 2023AV-NeRF: Learning Neural Fields for Real-World Audio-Visual Scene Synthesiscited by 49
  7. 2023Neural Acoustic Context Field: Rendering Realistic Room Impulse Response With Neural Fieldscited by 23
  8. 2024Real Acoustic Fields: An Audio-Visual Room Acoustics Dataset and Benchmarkcited by 20
  9. 2024Room impulse response reconstruction with physics-informed deep learningcited by 10
  10. 2023Implicit neural representation with physics-informed neural networks for the reconstruction of the early part of room impulse responsescited by 8
  11. 2019Towards Generating Ambisonics Using Audio-Visual Cue for Virtual Realitycited by 4

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