Objective Evaluation of Interior Noise Booming in a Passenger Car Based on Sound Metrics and Artificial Neural Networks

Booming sound is an important sound in a passenger car. This paper aims to develop the objective evaluation method of interior booming sound. The method is based on sound metrics and ANN (artificial neural network). The developed method is called the booming index. Prior work maintained that booming sound quality is related to loudness and sharpness–-the sound metrics used in psychoacoustics--and that the booming index is developed by using the loudness and sharpness for a signal within whole frequency between 20 Hz and 20 kHz. In this paper, the booming sound quality was found to be effectively related to the loudness at frequencies below 200 Hz; thus the booming index is updated by using the loudness of the signal filtered by the low pass filter at frequency under 200 Hz. The relationship between the booming index and sound metric is identified by an ANN. The updated booming index has been successfully applied to the objective evaluation of the booming sound quality of mass-produced passenger cars.

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  • Supplemental Notes:
    • Abstract reprinted with permission from Elsevier.
  • Authors:
    • Lee, Hyun-Ho
    • Lee, Sang-Kwon
  • Publication Date: 2009-9


  • English

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  • Accession Number: 01146411
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Dec 4 2009 2:39PM