  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.
