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Speech signal processing has become an important mode of interaction with computer. In this paper, Mel Frequency Cepstral Coefficient (MFCC) technique has been used to process speech samples to attain the recognition. MFCC is a term which narrate the short-term power spectrum of a speech signal, depend on a linear cosine transform (FFT and DCT we have used in our work) of a log power spectrum on a nonlinear Mel scale of frequency. We have used Dynamic Time Warping algorithm and Cross Correlation algorithm to match feature vectors. We have taken five recorded reference word through “One” to “Five”. Then the feature vectors generated from this reference signals are stored in database. A test sample of any numeric in “One” to “Five” is again recorded and then the algorithm is applied to recognize the same with recorded reference voices. In our paper, the recognition techniques show different …