• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.9
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• pp.993-1000
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• 2015

Mel-Frequency Cepstral Coefficients(: MFCC) is one of the noble feature vectors for speech signal processing. An evident drawback in MFCC is that the phase information is lost by taking the magnitude of the Fourier transform. In this paper, we consider a method of utilizing the phase information by treating the magnitudes of real and imaginary components of FFT separately. By applying this method to speech recognition with FVQ/HMM, the speech recognition error rate is found to decrease compared to the conventional MFCC. By numerical analysis, we show also that the optimal value of MFCC components is 12 which come from 6 real and imaginary components of FFT each.