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Vehicle Sound Pattern Recognition (SPR)
This project is no longer active.
Head: Mel Siegel
Mailing address:
Carnegie Mellon University
Robotics Institute
5000 Forbes Avenue
Pittsburgh, PA 15213
Associated center: CIMDS
Associated lab/group: Intelligent Sensor, Measurement, and Control Lab
For more information, see this project's homepage.
Almost every moving vehicle makes some kind of noise; the noise can come from the vibrations of the running engine, bumping and friction of the vehicle tires with the ground, wind effects, etc. Vehicles of the same kind and working in similar conditions (``class'') will generate similar noises, or have some kind of noise signature. This noise pattern gives a clue for military reconnaissance or a surveillance mission robot to detect a vehicle and recognize its class. Our research goal is to characterize noise patterns and use them to recognize whether a new detected sound is from a vehicle of known type, and if so to classify its type.
When travelling at different speeds, under different road conditions, or with different acceleration, a vehicle emits different noise patterns. These noises can be sampled or digitized and grouped in a series of time slices (frames); then if the spectrum changes with time, it can be described in the frequency domain as the change of frequency spectrum distribution over frames.
Note: This list may not be comprehensive. It contains only those publications in the RI publications database. Entries are listed in reverse chronological order.