Analysis of spectral interpolation with weighting dependent on frame energy

Spectral interpolation improves the performance of low bit rate speech coders without increasing the bit rate. We have investigated the problem of spectral interpolation, by means of autoregressive theory. Our analysis is supported by experiments on stationary and non-stationary data and by experiments on real speech data. The main conclusions of our study are: the energy of the analysis frames should be used in the interpolation process. It is beneficial to give analysis frames an overlap of p samples, where p is the order of the model. The reflection coefficients, log area ratios and the arcsine of reflection coefficients are less suitable for interpolation