Abstract
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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
