Comparative study between different classifiers based speaker recognition system using MFCC for noisy environment

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.

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