Showing papers on "Code-excited linear prediction published in 1977"
TL;DR: It is shown by theoretical argument and by experiment that selection of an undriven segment of voiced speech for analysis by linear predictive coding (LPC) gives more accurate estimates of the poles of the vocal-tract model.
Abstract: We show by theoretical argument and by experiment with both synthetic and real data that selection of an undriven segment of voiced speech for analysis by linear predictive coding (LPC) gives more accurate estimates of the poles of the vocal-tract model. In the case of voiced nasal phonemes, this technique provides a simple algorithm for separately determining the poles and the zeros in the model and illustrates the desirability of identifying the portions of the speech wave during which there is a significant driving input. A key problem which remains is the development of a practical algorithm for selecting such segments for analysis.
40 citations
01 Dec 1977
TL;DR: The covariance lattice linear prediction method is shown to have some advantages over the other methods for segmenting speech into regions where the spectrum is approximately stationary.
Abstract: Linear predictive analysis/synthesis methods offer an efficient means of low bit rate encoding of speech signals. This method involves the time segmentation of the speech into regions where the spectrum is approximately stationary. The analysis/ synthesis technique is discussed as well as four methods of determining linear predictive approximations A comparison of these methods on a synthetic speech-like signal and on real speech is presented. The covariance lattice linear prediction method is shown to have some advantages over the other methods for segmenting speech into regions where the spectrum is approximately stationary.
1 citations