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Effect of long-term time-varying loudness and duration on subjects’ ratings of startle evoked by shaped sonic booms and impulsive sounds

机译:长时间随时间变化的响度和持续时间对对象的惊吓等级的影响,这些惊吓等级是由异型的声音爆棚和冲动的声音引起的

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Statistics of Moore and Glasberg’s time-varying loudness and Zwicker’s sharpness have been found to accurately predict startle and annoyance evoked by low amplitude sonic booms. In a previous study by the authors where subjects judged the startle evoked by these sounds and boom-like amplitude modulated noise, regression models consisting of a statistic of maximum loudness (short-term or long-term), maximum sharpness and maximum loudness derivative predicted subject ratings the best. However, while most of the metric values of that stimulus set were weakly correlated, short-term and long-term loudness were highly correlated with each other. In addition, as the signals used in this dataset were very similar in duration (< 400 ms), it was unclear how well the models developed would predict startle evoked by longer sounds, such as sonic booms with echoes. To investigate these issues, another experiment was conducted where subjects were asked to judge the startle, annoyance and acceptability evoked by a series of sonic booms (with and without echoes), boom-like noises, distant gunfire, door slams and blast noise. The performance of these metrics as well as previously developed startle models will also be discussed.
机译:发现摩尔和格拉斯伯格的时变响度和Zwicker的清晰度可以准确预测低振幅声波引起的惊吓和烦恼。在作者先前的研究中,受试者判断这些声音和类似动臂的调幅噪声所引起的惊吓,回归模型由最大响度(短期或长期),最大清晰度和最大响度统计量的预测组成主题评分最高。但是,尽管该刺激集的大多数度量值之间的相关性很弱,但短期和长期响度却彼此高度相关。此外,由于此数据集中使用的信号持续时间非常短(<400毫秒),因此尚不清楚所开发的模型将如何预测较长声音(例如带有回声的音爆)引起的惊吓。为了调查这些问题,进行了另一项实验,要求受试者判断一系列声响(带有或不带有回声),类似吊杆的声音,遥远的枪声,门砰和爆炸声所引起的惊吓,烦恼和可接受性。这些指标的性能以及先前开发的惊吓模型也将进行讨论。

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    《》|2015年|1-7|共7页
  • 会议地点 San Francisco CA(US)
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    Ray W. Herrick LaboratoriesPurdue University170 S. Martin Jischke Dr.West Lafayette IN USA email: amarshall@swri.org;

    Ray W. Herrick LaboratoriesPurdue University170 S. Martin Jischke Dr.West Lafayette IN USA email: daviesp@purdue.edu;

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