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Objective sound quality evaluation for the vehicle interior noise based on responses of the basilar membrane in the human ear

机译:基于人耳基底膜响应的车辆内部噪声的客观音质评价

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摘要

The paper proposes a new method for objective sound quality evaluation for the vehicle interior noise based on the displacement of the basilar membrane in the human ear. The method was mainly carried out in four steps. Firstly, the noise samples in different seats of a car under different working conditions were collected through the vehicle interior noise test. Secondly, the subjective evaluation values (SEVs) of the noise samples were obtained by the adaptive grouped paired comparison method. In the third step, the statistical mean values of the basilar membrane displacement responses (SMVBMDR) were calculated in a lumped-parameter model of the human ear, and thereby a SMVBMDR-based feature matrix was established. Finally, taking the traditional psychoacoustic metrics and the extracted feature matrix as input, two BP neural network models for sound quality evaluation for the vehicle interior noise were established, respectively. To verify effectiveness of the new metric SMVBMDR, the correlations between this metric and the SEVs, as well as between the traditional psychoacoustic metrics and the SEVs were respectively analyzed. The results show that the SMVBDMDR has a higher correlation with the SEVs. Besides, the sound quality prediction of the model based on the SMVBMDR is more accurate than that of the model based on the traditional psychoacoustic metrics. The above results indicate that the new metric SMVBMDR can be used as an effective physiological acoustic metric for objective sound quality evaluation for the vehicle interior noise. (C) 2020 Elsevier Ltd. All rights reserved.
机译:本文提出了一种基于人耳基底膜位移的车辆内部噪声的客观声音质量评价的新方法。该方法主要以四个步骤进行。首先,通过车辆内部噪声测试收集不同工作条件下汽车不同座位的噪声样本。其次,通过自适应分组配对的比较方法获得噪声样本的主观评估值(SEV)。在第三步中,基础膜位移应答(SMVBMDR)的统计平均值在人耳的一大块参数模型中计算,从而建立了基于SMVBMDR的特征矩阵。最后,采用传统的心理声学指标和提取的特征矩阵作为输入,分别建立了用于车辆内部噪声的音质评估的两个BP神经网络模型。为了验证新的公制SMVBMDR的有效性,分别分析了该度量和SEVS之间的相关性以及传统的心理声学度量和SED之间的相关性。结果表明,SMVBDMDR与SED具有更高的相关性。此外,基于SMVBMDR的模型的音质预测比传统心理声学指标的模型更准确。上述结果表明,新的公制SMVBMDR可以用作车辆内部噪声的客观声音质量评估的有效生理声学指标。 (c)2020 elestvier有限公司保留所有权利。

著录项

  • 来源
    《Applied Acoustics》 |2021年第1期|107619.1-107619.13|共13页
  • 作者单位

    China Univ Min & Technol Sch Mechatron Engn 1 Daxue Rd Xuzhou 221116 Jiangsu Peoples R China;

    Chongqing Changzheng Heavy Ind Co Ltd Chongqing 400083 Peoples R China;

    China Univ Min & Technol Sch Mechatron Engn 1 Daxue Rd Xuzhou 221116 Jiangsu Peoples R China;

    China Univ Min & Technol Sch Mechatron Engn 1 Daxue Rd Xuzhou 221116 Jiangsu Peoples R China;

    China Univ Min & Technol Sch Mechatron Engn 1 Daxue Rd Xuzhou 221116 Jiangsu Peoples R China;

    China Univ Min & Technol Sch Mechatron Engn 1 Daxue Rd Xuzhou 221116 Jiangsu Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Sound quality; Vehicle interior noise; Objective evaluation; Basilar membrane; BP neural network;

    机译:音质;车辆内部噪声;客观评估;基底膜;BP神经网络;

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