DocumentCode :
3729309
Title :
Comparative study between different classifiers based speaker recognition system using MFCC for noisy environment
Author :
Abhilasha Sukhwal;Mahendra Kumar
Author_Institution :
Rajasthan College of Engg. for Women, Jaipur, India
fYear :
2015
Firstpage :
955
Lastpage :
960
Abstract :
Speaker recognition has made great progress under the laboratory environment, but in real life the performance of speaker recognition system is affected by various factors including environmental noise. This paper studies the performance of speaker recognition system in noisy environment and presents Speaker recognition system using Mel-Frequency Cepstral Coefficients (MFCC) technique based on different classifiers likes Euclidean distance, Back-Propagation Neural Network (BPNN), Self Organizing Map (SOM). This paper presents comparative plots of different classifier. Speaker recognition system based on SOM Neural Network classifier is provide better recognition rate compare to BPNN and Euclidean Distance based systems.
Keywords :
"Speaker recognition","Training","Testing","Mel frequency cepstral coefficient","Feature extraction","Euclidean distance","Neurons"
Publisher :
ieee
Conference_Titel :
Green Computing and Internet of Things (ICGCIoT), 2015 International Conference on
Type :
conf
DOI :
10.1109/ICGCIoT.2015.7380600
Filename :
7380600
Link To Document :
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