Landmark-based audio fingerprinting system applied to vehicle squeak and rattle noises

• Oleksandr Pogorilyi ^[1] ; Mohammad Fard ^[1] ; David Taylor ^[1] ; John Davy ^[1]
  1. [1] School of Engineering Melbourne
• Localización: Noise Control Engineering Journal, ISSN 0736-2501, Vol. 68, Nº. 2, 2020, págs. 113-124
• Idioma: inglés
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• Resumen

  • This article investigates whether the robust landmark-based audio fingerprinting method created for recognizing music can be applied to identify squeak and rattle (S&R) types of sounds. The identification is performed by matching a query audio sample to the perceptually closest audio sample that is stored in a pre-developed database of S&R audio sounds. The aim of the application of the method in the automotive industry is to facilitate the process S&R experts go through during sound identification. The experimental results show that the algorithm can be used for identification of different types of S&R sounds when the audio database contains a limited number of reference samples.