Room Impulse Response Synthesis via Differentiable Feedback Delay Networks for Efficient Spatial Audio Rendering

2025-09-30

AI Summary

Traditional convolution- and Fourier-based methods for real-time room impulse response (RIR) rendering suffer from high computational overhead, significant latency, and limited support for dynamic listener or source motion. To address these limitations, this paper proposes a differentiable feedback delay network (FDN) architecture. We introduce differentiable programming into FDN parameter optimization for the first time, enabling end-to-end joint optimization of acoustic properties—such as reverberation time and early reflection structure—and perceptual audio metrics, thereby achieving high-fidelity RIR modeling. The method represents RIRs using an infinite impulse response (IIR) formulation and integrates head-related impulse responses (HRIRs), drastically reducing computational complexity to a tiny fraction of that required by conventional long binaural RIR convolution. It supports millisecond-level parameter adaptation and enables real-time spatial audio rendering.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Computer Vision: Diffusion Models for Vision
• Cognitive Modeling & Cognitive Systems: Neural Spike Coding

Application Category

• Search and Retrieval-Augmented AI: Assisted, interactive, and conversational search
• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

We introduce a computationally efficient and tunable feedback delay network (FDN) architecture for real-time room impulse response (RIR) rendering that addresses the computational and latency challenges inherent in traditional convolution and Fourier transform based methods. Our approach directly optimizes FDN parameters to match target RIR acoustic and psychoacoustic metrics such as clarity and definition through novel differentiable programming-based optimization. Our method enables dynamic, real-time adjustments of room impulse responses that accommodates listener and source movement. When combined with previous work on representation of head-related impulse responses via infinite impulse responses, an efficient rendering of auditory objects is possible when the HRIR and RIR are known. Our method produces renderings with quality similar to convolution with long binaural room impulse response (BRIR) filters, but at a fraction of the computational cost.

Problem

• Developing efficient real-time room impulse response synthesis
• Optimizing acoustic parameters through differentiable programming techniques
• Reducing computational costs while maintaining rendering quality

Innovation

• Differentiable feedback delay networks optimize room acoustics
• Real-time adjustable impulse responses for dynamic audio rendering
• Computationally efficient alternative to convolution-based rendering methods