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Probabilistic modeling framework for multisource sound mapping

机译：多源声音映射的概率建模框架

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The process of modeling noise maps is now well defined: long-term aggregated indicators are calculated based on a collection or estimation of road, air and rail traffic variables. This framework however disregards the sound levels variations, and hence prevents the production of statistical or emergence indicators, and does not allow for the study of competition between typical urban sound sources that can improve the characterization of urban sound environments. A modeling framework in four steps is proposed to answer these issues: (i) a spatial distribution of the potential sound source of interest, (ii) the calculation of a sound propagation matrix, (iii) the stochastic activation of a sound sources ratio for n iterations of the sound map, and (iv) the calculation of specific sound indicators. The stochastic approach proposed in this study enables the estimation of the temporal sound distribution per sound source. It permits in particular to deduce source-oriented indicators such as the percentage of the time when a given sound source emerges from an urban sound mixture. An example of application of this framework is exposed for a district in the city of Nantes, France. It shows the interest of such approaches, in particular for soundscape and urban sound environment studies.
机译：现在已经很好地定义了噪声图的建模过程：基于对道路，空中和铁路交通变量的收集或估计，计算了长期汇总指标。然而，该框架无视声级变化，因此阻止了统计或紧急指标的产生，并且不允许研究可改善城市声环境特征的典型城市声源之间的竞争。建议通过四个步骤的建模框架来回答这些问题：（i）潜在潜在声源的空间分布，（ii）声音传播矩阵的计算，（iii）随机激活声源比声音图的n次迭代，以及（iv）特定声音指示器的计算。在这项研究中提出的随机方法能够估计每个声源的时间声音分布。它尤其允许推导面向源的指标，例如从城市声音混合中出现给定声源的时间百分比。在法国南特市的一个区域中公开了此框架的应用示例。它显示了这种方法的兴趣，特别是对于声音景观和城市声音环境研究。

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