Ill-conditioning and bandwidth expansion in linear prediction of speech

This paper examines schemes that modify linear prediction (LP) analysis for speech signals. First, techniques which improve the conditioning of the LP equations are examined. White noise compensation for the correlations is justified from the point of view of reducing the range of values which the predictor coefficients take on. The efficacy of the procedure is measured over a large speech database. Various techniques for bandwidth expansion of the LP spectral peaks are also examined. These include lag windowing of the correlation, windowing of the predictor coefficients, and modification of the line spectral frequencies. New formulas for the bandwidth expansion factor are given.