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Combining Ray Tracing and SEA to Predict Speech Transmissibility
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<div class="section abstract"><div class="htmlview paragraph">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.</div></div>
Title: Combining Ray Tracing and SEA to Predict Speech Transmissibility
Description:
<div class="section abstract"><div class="htmlview paragraph">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.
</div></div>.
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