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 in estimating the vocal tract parameters of voiced speech. In order to overcome this, 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 a wavelet transform of the speech signals, the interval of adjacent two GCIs 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 the GCI than any other time in a pitch period. We select those samples which are far from the 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 the 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