The Burg algorithm for LPC speech analysis/Synthesis

The performance of the Burg method for speech analysis is compared to the autocorrelation and covariance methods. The criterion of goodness is the accuracy of the spectral approximation, filter stability, windowing requirements, data frame length, and spectral resolution. A mathematical comparison is presented for the simple first-order signal. Spectral comparisons are presented for a second-order speech-like signal. Real speech synthesis using the analysis results of the autocorrelation and Burg methods are subjectively compared. The results do not find any justification for preferring the computationally more complex Burg method.