...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Applied Acoustics >Research and development of sound quality in portable testing and evaluation system based on self-adaptive neural network
【24h】

Research and development of sound quality in portable testing and evaluation system based on self-adaptive neural network

机译：基于自适应神经网络的便携式测试评估系统的音质研究与开发

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Ordinary microphone cannot accurately reflect authentic human feelings in the sound quality testing and evaluation. By contrast, professional artificial head system can produce similar results with human feelings through the simulation of human auditory system, but it is expensive and unable to occupy the driver's seat to record the vehicle sound. Here we design a portable system based on self-adaptive neural network (NN) which can obtain the result of sound quality evaluation similar with the artificial head. The system consists of binaural microphone, signal conditioning units (SCU), and mobile phone. Firstly, sound is perceived by binaural microphone, processed by SCU, and collected by mobile phone. Initial sound quality objective parameters are calculated after noise reduction for sound signals and then the accurate objective parameters can be obtained from the initial parameters through the trained NN model. To train the model, the portable system and the HEAD system are simultaneously used to collect sound sample as the input and output sample sets under different conditions. After the input samples are preprocessed, wavelet entropy eigenvalues based on the best tree wavelet packet analysis are calculated along with psychoacoustic parameters of all the samples. Finally, we obtain the combined feature vectors and successfully train the model. Checked by the practical data, the relative error of sound quality objective parameters produced by the NN model is less than 5% compared with the HEAD system, which conforms to general engineering requirements. This inexpensive and user-friendly portable system paves a new way in the sound quality testing and evaluation that are highly desirable for vehicle acoustical designs and improvements. (C) 2019 Elsevier Ltd. All rights reserved.
机译：普通麦克风无法在音质测试和评估中准确反映真实的人为感觉。相比之下，专业的人工头部系统可以通过模拟人的听觉系统产生与人的感觉相似的结果，但是它昂贵且无法占据驾驶员的座位来记录车辆的声音。在这里，我们设计了一个基于自适应神经网络（NN）的便携式系统，该系统可以获得与人工头类似的声音质量评估结果。该系统由双耳麦克风，信号调节单元（SCU）和移动电话组成。首先，声音由双耳麦克风感知，由SCU处理并由手机收集。在对声音信号进行降噪之后，计算初始声音质量目标参数，然后可以通过训练后的NN模型从初始参数中获得准确的目标参数。为了训练模型，便携式系统和HEAD系统同时用于收集声音样本作为不同条件下的输入和输出样本集。在对输入样本进行预处理之后，将基于最佳树小波包分析以及所有样本的心理声学参数计算出小波熵特征值。最后，我们获得了组合的特征向量并成功地训练了模型。经实际数据检验，与HEAD系统相比，NN模型产生的音质目标参数的相对误差小于5％。这种廉价且用户友好的便携式系统在声音质量测试和评估方面开辟了一条新途径，这是汽车声学设计和改进的高度希望。 （C）2019 Elsevier Ltd.保留所有权利。

著录项

  • 来源
    《Applied Acoustics》 |2019年第11期|138-147|共10页
  • 作者

    Xie Xiaoping; Ma Zhiyuan; Ye Jinyi; Zeng Fandong; Fan Wenchao; Chen Bingan;

  • 作者单位

    Hunan Univ, Coll Mech & Vehicle Engn, State Key Lab Adv Design & Mfg Vehicle Body, Changsha 410082, Hunan, Peoples R China;

    Hunan Univ, Coll Mech & Vehicle Engn, State Key Lab Adv Design & Mfg Vehicle Body, Changsha 410082, Hunan, Peoples R China;

    Hunan Univ, Coll Mech & Vehicle Engn, State Key Lab Adv Design & Mfg Vehicle Body, Changsha 410082, Hunan, Peoples R China;

    Hunan Univ, Coll Mech & Vehicle Engn, State Key Lab Adv Design & Mfg Vehicle Body, Changsha 410082, Hunan, Peoples R China;

    Hunan Univ, Coll Mech & Vehicle Engn, State Key Lab Adv Design & Mfg Vehicle Body, Changsha 410082, Hunan, Peoples R China;

    Hunan Univ, Coll Mech & Vehicle Engn, State Key Lab Adv Design & Mfg Vehicle Body, Changsha 410082, Hunan, 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 evaluation; Sound quality testing system; Sound quality objective parameters; Self-adaptive neural network; Wavelet entropy;

    机译：声音质量评估;声音质量测试系统;声音质量目标参数;自适应神经网络;小波熵;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号