Oleksandr Pogorilyi
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Mohammad Fard
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John Davy
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Mechanical and Automotive Engineering, School
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Mechanical and Automotive Engineering, School
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...
In this article, an artificial neural network is proposed to classify short audio sequences of squeak and rattle (S&R) noises. The aim of the classification is to see how accurately the trained classifier can recognize different types of S&R sounds. Having a high accuracy model
that can recognize audible S&R noises could help to build an automatic tool able to identify unpleasant vehicle interior sounds in a matter of seconds from a short audio recording of the sounds. In this article, the training method of the classifier is proposed, and the results show that
the trained model can identify various classes of S&R noises: simple (binary clas- sification) and complex ones (multi class classification).
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