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