NDLI: Automatic noise recognition based on neural network using LPC and MFCC feature parameters

Content Provider	IEEE Xplore Digital Library
Author	Haghmaram, R. Aroudi, A. Ghezel, M.H. Veisi, H.
Copyright Year	2012
Description	Author affiliation: Department of Computer, Engineering, Sharif University of Technology, Tehran, Iran (Veisi, H.) \|\| Department of Electrical, Engineering, IHU, Tehran, Iran (Haghmaram, R.; Aroudi, A.) \|\| Aiagh, Department of Electrical, Engineering, IHU, Tehran, Iran (Ghezel, M.H.)
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 coefficients goes afterward with 99.0% of accuracy.
Starting Page	69
Ending Page	73
File Size	363608
Page Count	5
File Format	PDF
ISBN	9781467307086
e-ISBN	9788360810484
e-ISBN	9788360810514
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-09-09
Publisher Place	Poland
Access Restriction	Subscribed
Rights Holder	Polish Info Processing Socit
Subject Keyword	Training Accuracy Noise Neurons Radial basis function networks Mel frequency cepstral coefficient Biological neural networks
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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