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|Title: ||Moving vehicle noise classification using backpropagation algorithm|
|Authors: ||Norasmadi, Abdul Rahim|
Paulraj, Murugesa Pandiyan, Assoc. Prof.
Abdul Hamid, Adom, Assoc. Prof. Dr.
|Keywords: ||Backpropagation;Feature extraction;Hearing impaired;Noise classification|
|Issue Date: ||21-May-2010|
|Publisher: ||Institute of Electrical and Electronics Engineers (IEEE)|
|Citation: ||p. 1-6|
|Series/Report no.: ||Proceedings of the 6th International Colloquium on Signal Processing and Its Applications (CSPA) 2010|
|Abstract: ||The hearing impaired is afraid of walking along a street and living a life alone. Since it is difficult for hearing impaired to hear and judge sound information and they often encounter risky situations while they are in outdoors. The sound produced by moving vehicle in outdoor situation cannot be moderate wisely by profoundly deaf people. They also cannot distinguish the type and the distance of any moving vehicle approaching from their behind. Generally the profoundly deaf people do not use any hearing aid which does not provide any benefit. In this paper, a simple system that identifies the type and distance of a moving vehicle using artificial neural network has been proposed. The noises emanated from moving vehicles along the roadside were recorded along with the type and distance of moving vehicles. Simple feature extraction algorithm for extracting the feature from noise emanated by the moving vehicle has been made using frequency analysis approach. A onethird- octave filter bands is used for getting the important signatures from the emanated noise. The extracted features are associated with the type and distance of the moving vehicle and a simple neural network model is developed. The developed neural network model is tested for its validity.|
|Description: ||Link to publisher's homepage at http://ieeexplore.ieee.org/|
|Appears in Collections:||Paulraj Murugesa Pandiyan, Prof. Dr.|
Abdul Hamid Adom, Prof. Dr.
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