The generalized cepstral analysis method is viewed as a unified approach to the cepstral method and the linear prediction method, in which the model spectrum varies continuously from all-pole to cepstral according to the value of a parameter 7. Since the human ear has high resolution at low frequencies, introducing similar characteristics to the model spectrum, we can represent speech spectrum more efficiently. From this point of view, this paper proposes a spectral estimation method which uses the spectral model represented by mel-generalized cepstral coefficients. The effectiveness of mel-generalized cepstral analysis is demonstrated by an experiment of HMM-based isolated word recognition.