Statistical Evaluation and Regression Analysis of Vehicle Sound Quality

A statistical approach to evaluate the subjective perception of the annoyance caused by the vehicle noise was presented in this paper. After recording the noises of Sanfeng, Huali and Xiali at speeds of 30, 40, 50, 60, 70 and 80 km/h respectively, the annoyance of the vehicle noises was evaluated in the testing room using paired comparison method, and the sound quality metrics and subjective annoyance were then distilled. Loudness, sharpness, roughness, periodicity and impulsiveness were selected for each of the vehicle noises. By correlation analysis method, it can be found that loudness has a higher correlation （0.91） with annoyance than other parameters. Meanwhile, sharpness, periodicity, roughness and impulsiveness have correlation with subjective perception with correlation coefficients being 0.84, -0.82, 0.62 and 0.87, respectively. The result of multiple regression analysis shows that calculated annoyance obtained by the regression equation can explain the perceptual annoyance and the regressed evaluation model is feasible to evaluate the sound quality of vehicle.

评估车辆噪音引起的烦恼的主观感觉的一条统计途径在这篇论文被介绍。在分别地以 30， 40， 50， 60， 70 和 80 km/h 的速度记录 Sanfeng， Huali 和 Xiali 的噪音以后，车辆噪音的烦恼用配对的比较方法，和声音质量度量标准和主观烦恼在严峻的房间里被评估然后被提取。大声，清晰度，粗糙，频率和冲动为每车辆噪音被选择。由关联分析方法，大声比另外的参数与烦恼有更高的关联(0.91 ) ，这能被发现。同时，清晰度，频率，粗糙和冲动与是的关联系数与主观感觉有关联 0.84， -0.82, 0.62 和 0.87 分别地。多重回归分析的结果显示出外出方程能向感性的烦恼解释的 ther 获得的那计算烦恼， regressed 评估模型是可行的评估车辆的声音质量。