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Enhanced Voice Recognition Using MFCC & K-Means by usha kumari is a document available to read on EtoBox.

This research proposal outlines the development of an improved voice recognition system utilizing Mel Frequency Cepstral Coefficients (MFCC) for feature extraction and K-Means algorithm for feature matching. The system aims to enhance security applications by accurately identifying speakers based on their voice characteristics. The study will also evaluate existing voice recognition systems and propose an efficient methodology for implementation using MATLAB.

Author
usha kumari
Language
EN