Durham School of Architectural Engineering and Construction, University of Nebraska-Lincoln, 1110 South 67th Street, Omaha, Nebraska 68182, USA.
J Acoust Soc Am. 2018 May;143(5):2697. doi: 10.1121/1.5036731.
This paper develops a model to predict if listeners would be likely to complain due to annoyance when exposed to a certain noise signal with a prominent tone, such as those commonly produced by heating, ventilation, and air-conditioning systems. Twenty participants completed digit span tasks while exposed in a controlled lab to noise signals with differing levels of tones, ranging from 125 to 1000 Hz, and overall loudness. After completing the digit span tasks under each noise signal, from which task accuracy and speed of completion were captured, subjects were asked to rate level of annoyance and indicate the likelihood of complaining about the noise. Results show that greater tonality in noise has statistically significant effects on task performance by increasing the time it takes for participants to complete the digit span task; no statistically significant effects were found on task accuracy. A logistic regression model was developed to relate the subjective annoyance responses to two noise metrics, the stationary Loudness and Tonal Audibility, selected for the model due to high correlations with annoyance responses. The percentage of complaints model showed better performance and reliability over the percentage of highly annoyed or annoyed.
本文开发了一个模型，以预测当听众暴露于具有突出音调的特定噪声信号（例如常见的加热、通风和空调系统产生的噪声）时，他们是否可能因烦恼而投诉。二十名参与者在受控实验室中完成了数字跨度任务，同时暴露于具有不同音调水平（从 125 到 1000 Hz）和总响度的噪声信号下。在完成每个噪声信号下的数字跨度任务后，从任务准确性和完成速度中捕获，参与者被要求评估烦恼程度并表示对噪声投诉的可能性。结果表明，噪声的更大音调性通过增加参与者完成数字跨度任务所需的时间对任务表现具有统计学上的显著影响；在任务准确性方面没有发现统计学上的显著影响。开发了一个逻辑回归模型，将主观烦恼反应与两个噪声指标相关联，由于与烦恼反应高度相关，因此选择了固定响度和音调可听度作为模型中的指标。投诉百分比模型在性能和可靠性方面均优于高度烦恼或烦恼的百分比模型。
