This contribution introduces a dataset of 7th-order Ambisonic Room Impulse Responses (HOA-RIRs), created using the Image Source Method. By employing higher-order Ambisonics, our dataset enables precise spatial audio reproduction, a critical requirement for realistic immersive audio applications. Leveraging the virtual simulation, we present a unique microphone configuration, based on the superposition principle, designed to optimize sound field coverage while addressing the limitations of traditional microphone arrays. The presented 64-microphone configuration allows us to capture RIRs directly in the Spherical Harmonics domain. The dataset features a wide range of room configurations, encompassing variations in room geometry, acoustic absorption materials, and source-receiver distances. A detailed description of the simulation setup is provided alongside for an accurate reproduction. The dataset serves as a vital resource for researchers working on spatial audio, particularly in applications involving machine learning to improve room acoustics modeling and sound field synthesis. It further provides a very high level of spatial resolution and realism crucial for tasks such as source localization, reverberation prediction, and immersive sound reproduction.

翻译：本研究介绍了一个基于镜像源法生成的七阶Ambisonic房间脉冲响应（HOA-RIRs）数据集。通过采用高阶Ambisonics技术，本数据集能够实现精确的空间音频重放，这是实现逼真沉浸式音频应用的关键要求。借助虚拟仿真技术，我们提出了一种基于叠加原理的独特麦克风配置方案，该方案旨在优化声场覆盖范围，同时解决传统麦克风阵列的局限性。所提出的64麦克风配置使我们能够直接在球谐函数域中捕获房间脉冲响应。数据集涵盖多种房间配置，包括房间几何形状、吸声材料及声源-接收器距离的变化。为准确复现实验，我们同时提供了仿真设置的详细说明。该数据集为空间音频领域的研究人员提供了重要资源，特别是在利用机器学习改进房间声学建模和声场合成的应用中。此外，数据集提供的极高空间分辨率和真实感，对于声源定位、混响预测和沉浸式声音重放等任务至关重要。