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OtoMechanic: Auditory Automobile Diagnostics via Query-by-Example

Authors: Morrison, Max
Pardo, Bryan
Date Issued: Oct-2019
Citation: M. Morrison & B. Pardo, "OtoMechanic: Auditory Automobile Diagnostics via Query-by-Example", Proceedings of the Detection and Classification of Acoustic Scenes and Events 2019 Workshop (DCASE2019), pages 169–173, New York University, NY, USA, Oct. 2019
Abstract: Early detection and repair of failing components in automobiles reduces the risk of vehicle failure in life-threatening situations. Many automobile components in need of repair produce characteristic sounds. For example, loose drive belts emit a high-pitched squeaking sound, and bad starter motors have a characteristic whirring or clicking noise. Often drivers can tell that the sound of their car is not normal, but may not be able to identify the cause. To mitigate this knowledge gap, we have developed OtoMechanic, a web application to detect and diagnose vehicle component issues from their corresponding sounds. It compares a user's recording of a problematic sound to a database of annotated sounds caused by failing automobile components. OtoMechanic returns the most similar sounds, and provides weblinks for more information on the diagnosis associated with each sound, along with an estimate of the similarity of each retrieved sound. In user studies, we find that OtoMechanic significantly increases diagnostic accuracy relative to a baseline accuracy of consumer performance.
First Page: 169
Last Page: 173
Type: Article
Appears in Collections:Proceedings of the Detection and Classification of Acoustic Scenes and Events 2019 Workshop (DCASE2019)

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