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Combining Ray Tracing and SEA to Predict Speech Transmissibility

机译:结合光线跟踪和海上预测语音传播性

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Speech transmissibility is a critical factor in the design of public address systems for passenger cabins in trains, aircraft and coaches. Speech transmissibility is primarily affected by the direct field, early low order reflections, and late reflections (reverberation) of the source. The direct and low order reflections are affected by the relative location of speakers and seats as well as the acoustic properties of the reflecting walls. To properly capture these early reflections, measures of speech transmissibility typically require time domain information. However, another important factor for speech transmissibility is background noise due to broadband exterior sources such as a flow noise sources. The background noise is typically modeled with broadband steady state assumptions such as in statistical energy analysis (SEA). This works presents an efficient method for predicting speech transmissiblity by combining ray tracing with SEA. In this method, the direct field and low order reflections are modelled using raytracing, while the reverberant field and background noise are modelled using SEA. Detailed models of the sound package are considered to accurately predict low order reflections. In this paper, the method is presented and the importance of the the detailed sound package model is demonstrated.
机译:语音传输是列车,飞机和教练乘客小屋的公共地址系统设计的关键因素。语音传播性主要受到源的直接场,早期低阶反射和后期反射(混响)的影响。直接和低阶反射受扬声器和座椅的相对位置的影响以及反射壁的声学特性。为了适当地捕获这些早期反射,语音传输的测量通常需要时域信息。然而,由于诸如流噪声源的宽带外部来源,另一个语音传播性的重要因素是背景噪声。背景噪声通常以宽带稳态假设建模,例如在统计能量分析(SEA)中。该作品通过将射线跟踪与大海组合来提出了一种有效的方法,用于预测语音透射性。在该方法中,使用光线结构建模直接字段和低阶反射,而混响场和背景噪声使用海。声音包的详细模型被认为是准确地预测低阶反射。在本文中,提出了该方法,并说明了详细的声音包模型的重要性。

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