A speech recognition system for the English alphabetPublic
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The goal of this study was to design a system that would facilitate word processing for the handicapped, and implement the general public's most natural and effective way of communication--verbally. The word processor recognized the letters of the alphabet. This project explored and tested three methods of feature extraction which were the DFT, Spectrogram, and MFCCs. It was shown that the MFCC provides the best feature vector with a recognition rate of 97.9%.
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