Abstract Participatory measurement of environmental sound levels has gained interest in recent years. The calibration of measuring instruments is currently the main technical limitation. It is often the responsibility of the users and can be a potential source of error or add costs to the measurement protocol. In this article, a calibration protocol is proposed, based on the low variability of the average noise emission of individual vehicles. The advantage of this protocol for the user is that it does not require specific equipment, i.e. reference sound source or device, or special knowledge in acoustics. The method consists in measuring the noise level of a few vehicles as they pass through at different measuring points. The measured levels are compared to the levels expected by a numerical model, the difference serving as an offset for subsequent measurements. The robustness of the protocol is first tested over a large experimental campaign, and it turns out that measuring the passage of 15 vehicles at 3 different locations limits the error to −1.8 ± 1.0 dB(A). Then, the protocol is tested in real conditions with a set of 8 smartphones. The comparison with a class 1 sound level meter on 6 control points shows an average error on all phones of −0.6 ± 1.2 dB(A).

中文翻译：

---

基于智能手机的声音测量应用的原位声学校准方法

摘要 近年来，环境声级的参与式测量引起了人们的兴趣。测量仪器的校准是目前主要的技术限制。这通常是用户的责任，并且可能是潜在的错误来源或增加测量协议的成本。在本文中，基于单个车辆平均噪声排放的低可变性，提出了一种校准协议。该协议对用户的优势在于它不需要特定设备，即参考声源或设备，或声学方面的特殊知识。该方法包括测量一些车辆在不同测量点通过时的噪音水平。将测量的水平与数值模型预期的水平进行比较，差值作为后续测量的偏移量。该协议的稳健性首先在大型实验活动中进行了测试，结果表明测量 3 个不同位置的 15 辆车的通过将误差限制在 -1.8 ± 1.0 dB(A)。然后，使用一组 8 部智能手机在真实条件下测试该协议。与 1 类声级计在 6 个控制点上的比较显示，所有手机的平均误差为 -0.6 ± 1.2 dB(A)。