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Automatic noise recognition based on neural network using LPC and MFCC feature parameters
, Article 2012 Federated Conference on Computer Science and Information Systems, FedCSIS 2012, 9 September 2012 through 12 September 2012 ; 2012 , Pages 69-73 ; 9781467307086 (ISBN) ; Aroudi, A ; Ghezel, M. H ; Veisi, H ; Sharif University of Technology
2012
Abstract
This paper studies the automatic noise recognition problem based on RBF and MLP neural networks classifiers using linear predictive and Mel-frequency cepstral coefficients (LPC and MFCC). We first briefly review the architecture of each network as automatic noise recognition (ANR) approach, then, compare them to each other and investigate factors and criteria that influence final recognition performance. The proposed networks are evaluated on 15 stationary and non-stationary types of noises with frame length of 20 ms in term of correct classification rate. The results demonstrate that the MLP network using LPCs is a precise ANR with accuracy rate of 99.9%, while the RBF network with MFCCs...