Spectral estimation of speech by mel‐generalized cepstral analysis

AbstractThis paper proposes a spectral estimation method of speech based on mel‐generalized cepstral representation. The spectral estimation based on generalized cepstral representation is a method that unifies the cepstral method and the linear prediction method. By this method, the spectral model can be varied continuously from the all‐pole model to the exponential model.This paper also discusses the following: the method of spectral estimation, where the mel‐generalized cepstrum is used instead of the generalized cepstrum; the uniqueness of the solution for the minimization problem; the solution method; and the convergence of the solution. The proposed method has the same features as those of the method based on the generalized cepstrum where the spectral model can be varied continuously and the stability of the obtained transfer function is guaranteed. Another feature is that characteristics similar to the human auditory sensation, i.e., the high resolution in the low‐frequency range and the coarse resolution in the high‐frequency range, are obtained since the mel‐generalized cepstrum is used as the parameter, which is the generalized cepstrum defined on the mel‐frequency axis. Finally, the features and the effectiveness of the proposed method is demonstrated by analysis examples of the synthesized signals and natural speech.