Acoustic Signature Recognition Of Moving Vehicles Using Elman Neural Network

Hearing impaired people cannot distinguish the sound of moving vehicles approaching them from behind. Since, it is difficult for hearing impaired to hear and judge sound information of vehicles, they often encounter risky situ- ations while they are outdoors. In this paper, a simple algorithm is proposed to classify the type and distance of the moving vehicles based on the sound signature. A simple experimental protocol is designed to record the vehicle sound under different environment conditions and also for different speed of the vehicles. The noise emanated from the moving vehicles along the roadside is recorded along with the type and distance of the ve- hicle. Autoregressive modeling algorithm is used to ex- tract features from the recorded sound signal. Elman neural network models are developed and trained using backpropagation algorithm to classify the vehicle type and its distance. The effectiveness of the network is vali- dated through simulation.