HiFi-HARP: A High-Fidelity 7th-Order Ambisonic Room Impulse Response Dataset

TL;DR

HiFi-HARP is a comprehensive, high-fidelity dataset of over 100,000 7th-order Ambisonic room impulse responses generated through hybrid simulation, enabling advanced research in spatial audio and room acoustics.

Contribution

It introduces a large-scale, realistic RIR dataset combining wave-based and ray-tracing simulations for high-order Ambisonics, surpassing prior collections in fidelity and complexity.

Findings

Provides detailed dataset statistics and comparison with existing collections.

Outlines potential benchmarks for spatial audio processing tasks.

Discusses machine learning applications and limitations of the dataset.

Abstract

We introduce HiFi-HARP, a large-scale dataset of 7th-order Higher-Order Ambisonic Room Impulse Responses (HOA-RIRs) consisting of more than 100,000 RIRs generated via a hybrid acoustic simulation in realistic indoor scenes. HiFi-HARP combines geometrically complex, furnished room models from the 3D-FRONT repository with a hybrid simulation pipeline: low-frequency wave-based simulation (finite-difference time-domain) up to 900 Hz is used, while high frequencies above 900 Hz are simulated using a ray-tracing approach. The combined raw RIRs are encoded into the spherical-harmonic domain (AmbiX ACN) for direct auralization. Our dataset extends prior work by providing 7th-order Ambisonic RIRs that combine wave-theoretic accuracy with realistic room content. We detail the generation pipeline (scene and material selection, array design, hybrid simulation, ambisonic encoding) and provide dataset statistics (room volumes, RT60 distributions, absorption properties). A comparison table highlights the novelty of HiFi-HARP relative to existing RIR collections. Finally, we outline potential benchmarks such as FOA-to-HOA upsampling, source localization, and dereverberation. We discuss machine learning use cases (spatial audio rendering, acoustic parameter estimation) and limitations (e.g., simulation approximations, static scenes). Overall, HiFi-HARP offers a rich resource for developing spatial audio and acoustics algorithms in complex environments.