Acoustic Volume Rendering for Neural Impulse Response Fields (2411.06307v1)

Abstract: Realistic audio synthesis that captures accurate acoustic phenomena is essential for creating immersive experiences in virtual and augmented reality. Synthesizing the sound received at any position relies on the estimation of impulse response (IR), which characterizes how sound propagates in one scene along different paths before arriving at the listener's position. In this paper, we present Acoustic Volume Rendering (AVR), a novel approach that adapts volume rendering techniques to model acoustic impulse responses. While volume rendering has been successful in modeling radiance fields for images and neural scene representations, IRs present unique challenges as time-series signals. To address these challenges, we introduce frequency-domain volume rendering and use spherical integration to fit the IR measurements. Our method constructs an impulse response field that inherently encodes wave propagation principles and achieves state-of-the-art performance in synthesizing impulse responses for novel poses. Experiments show that AVR surpasses current leading methods by a substantial margin. Additionally, we develop an acoustic simulation platform, AcoustiX, which provides more accurate and realistic IR simulations than existing simulators. Code for AVR and AcoustiX are available at https://zitonglan.github.io/avr.

• The paper introduces Acoustic Volume Rendering (AVR) which adapts 3D volume rendering techniques for synthesizing precise acoustic impulse responses.
• It employs frequency-domain transforms and spherical integration to manage phase shifts and capture spatial audio features accurately.
• Empirical tests show AVR outperforms traditional methods, enabling zero-shot binaural audio synthesis for immersive realistic environments.

Acoustic Volume Rendering for Neural Impulse Response Fields

The paper introduces a new methodology, Acoustic Volume Rendering (AVR), aimed at enhancing impulse response (IR) modeling for audio synthesis by adapting volume rendering techniques to the acoustic domain. This research addresses the challenges of accurately synthesizing impulse responses, critical for immersive audio experiences in virtual and augmented reality.

Technical Contributions

The primary innovation presented in this work is the adaptation of volume rendering, traditionally applied in 3D scene rendering to the inherent characteristics of acoustic signals. Unlike visual signals, acoustic impulse responses function in the time domain and exhibit high spatial variation, necessitating a unique approach to rendering and signal processing.

1. Frequency-Domain Volume Rendering:
   • The authors transform impulse responses into the frequency domain using Fourier transforms, which aids in handling the time-series nature of impulse signals and their spatial variability.
   • This conversion enables effective management of phase shifts, thus accurately representing time delays without being constrained by finite time domain sampling.
2. Spherical Integration:
   • Ray-based spherical integration is employed to synthesize impulse responses from various spatial positions, integrating environmental and directional characteristics captured in impulse measurements.
   • This approach allows for personalized audio experiences, integrating head-related transfer functions (HRTFs) at inference time.
3. Framework for Wave Propagation:
   • Overall, AVR incorporates wave propagation principles intrinsic to sound transmission, ensuring consistency and accuracy across multiple auditory perspectives.

Additionally, a new simulation platform, AcoustiX, is developed alongside AVR to provide accurate impulse response simulations, addressing limitations of existing simulators that often generate inaccurate phase and arrival time data.

Numerical Results and Empirical Validation

The paper reports empirical evaluations demonstrating that AVR significantly surpasses existing methodologies in both real-world and simulated datasets. The evaluations include measures like phase and amplitude errors, clarity (C50), early decay time (EDT), and reverberation time (T60). AVR's capability to zero-shot render binaural audio, a task previous methods struggled with, underscores its practical utility and robustness. The system's performance is evidenced by comprehensive numerical results showing AVR's superiority in accurately generating impulse responses across different spatial configurations.

Implications and Future Directions

Theoretically, this research offers advancements in neural acoustic field modeling by incorporating acoustic properties and principles directly into rendering processes. Practically, it sets the stage for improved audio simulations in a variety of applications, including VR/AR environments and auditory scene analysis.

Looking forward, potential developments could explore the application of AVR in more dynamic and computationally constrained environments. Future work could leverage the flexibility of this method to generalize across novel scenes with minimal acoustic data reliance, possibly integrating with visual modalities for a more holistic environmental understanding.

The paper contributes to the field by addressing both the fundamental modeling challenges in acoustic signal processing and by offering a new tool for the synthesis of realistic audio environments. This work stands as a methodological bridge between neural scene synthesis and acoustic modeling, potentially driving significant advancements in auditory fidelity for sensory-rich applications.