A scheme for high quality linear prediction analysis of speech

Because of existence of pseudo-periodic excitation impulses, the conventional Linear prediction (LP) analysis is often not accurate on estimating vocal tract parameters of voiced speech. In order to overcome the shortage, we propose a scheme for high quality Linear prediction analysis of speech, it contains two main stages. First, the glottal closure instant (GCI) is detected using wavelet transform of speech signals, the interval of adjacent two GCI's is a pitch period, the LP analysis can be executed pitch-synchronously on one or several pitch periods. Second, the excitation impulses are much stronger around GCI than other time in a ;Pitch period. We select those samples which an far from GCI and LP analysis is executed on these selected samples rather than all samples in an analysis frame. The prediction errors of the selected samples become very small. Thus, the accuracy of estimating vocal tract parameters is improved significantly. The validity of the proposed method is confirmed by comparing the results obtained from the proposed and conventional LP analysis methods.