开源工具Binamix可生成大规模空间音频数据集，助力虚拟现实与音频研究。
Binamix -- A Python Library for Generating Binaural Audio Datasets
- 基于SADIE II数据库，支持程序化双耳混音与插值渲染
- 采用改进的Delaunay三角剖分实现非采样角度的精准响应插值
- 适合音频算法测试、模型训练及空间音频系统开发人员使用
虚拟现实、沉浸式媒体和空间音频研究对空间音频数据集的需求日益增长，亟需可靠的生成方案。Binamix是一款开源Python库，基于包含20名受试者头相关冲激响应（HRIR）和双耳房间冲激响应（BRIR）数据的SADIE II数据库，支持程序化双耳混音。该库提供灵活可重复的框架，用于构建大规模空间音频数据集，适用于编解码器评估、音频质量度量开发和机器学习模型训练。内置多种预设脚本、实用函数和可视化工具，简化自定义流程。支持方位角、仰角、受试者冲激响应、扬声器布局等多参数配置，结合改进的Delaunay三角剖分技术，可在无原始数据的角度上实现精确的HRIR/BRIR插值。该工具使研究人员能以可复现的方法推进空间音频应用。代码已开源，许可协议为Apache 2.0，地址：https://github.com/QxLabIreland/Binamix/
原文摘要 · Abstract (English)
The increasing demand for spatial audio in applications such as virtual reality, immersive media, and spatial audio research necessitates robust solutions to generate binaural audio data sets for use in testing and validation. Binamix is an open-source Python library designed to facilitate programmatic binaural mixing using the extensive SADIE II Database, which provides Head Related Impulse Response (HRIR) and Binaural Room Impulse Response (BRIR) data for 20 subjects. The Binamix library provides a flexible and repeatable framework for creating large-scale spatial audio datasets, making it an invaluable resource for codec evaluation, audio quality metric development, and machine learning model training. A range of pre-built example scripts, utility functions, and visualization plots further streamline the process of custom pipeline creation. This paper presents an overview of the library's capabilities, including binaural rendering, impulse response interpolation, and multi-track mixing for various speaker layouts. The tools utilize a modified Delaunay triangulation technique to achieve accurate HRIR/BRIR interpolation where desired angles are not present in the data. By supporting a wide range of parameters such as azimuth, elevation, subject Impulse Responses (IRs), speaker layouts, mixing controls, and more, the library enables researchers to create large binaural datasets for any downstream purpose. Binamix empowers researchers and developers to advance spatial audio applications with reproducible methodologies by offering an open-source solution for binaural rendering and dataset generation. We release the library under the Apache 2.0 License at https://github.com/QxLabIreland/Binamix/
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