Showing papers on "Code-excited linear prediction published in 1974"

A linear prediction vocoder simulation based upon the autocorrelation method

Abstract: A detailed discussion of the computer simulation of a linear prediction vocoder system is presented. The basic technique used for analysis is the autocorrelation method of linear prediction. New results include modifications to the simplified inverse filter tracking (SIFT) algorithm for more efficient pitch extraction, coding algorithms for low-bit rate transmission, a simplified synthesizer gain calculation, and a bias correction for the synthesizer driving function. Experimental results are presented which illustrate both the capabilities and limitations of linear prediction vocoders.

Selective Linear Prediction and Analysis-by-Synthesis in Speech Analysis

Abstract: : Linear prediction is presented as a spectral modeling technique in which the signal spectrum is modeled by an all-pole spectrum. The method allows for arbitrary spectral shaping in the frequency domain, and for modeling of continuous as well as discrete spectra (such as filter bank spectra). In addition, using the method of selective linear prediction, all-pole modeling is applied to selected portions of the spectrum, with applications to speech recognition and speech compression. Linear prediction is compared with traditional analysis-by-synthesis techniques for spectral modeling. It is found that linear prediction offers computational advantages over analysis-by- synthesis, as well as better modeling properties if the variations of the signal spectrum from the desired spectral model are large. For relatively smooth spectra and for filter bank spectra, analysis-by-synthesis is judged to give better results. Finally, a suboptimal solution to the problem of all-zero modeling using linear prediction is given.