Spectral envelope sampling and interpolation in linear predictive analysis of speech

In spite of its extensive use, speech analysis based on linear prediction (LP) is liable to various causes of inaccuracy. This paper presents a novel approach to improve the accuracy in the estimation of the voiced speech production model based on the LP method. The presented method uses interpolation between spectral points which are least influenced by artifacts in the spectral analysis and by noise in the signal. We show, on analyses of both synthetic and natural speech, that the averaged parabolic approximation between harmonic peaks of voiced speech spectrum reduces the sensitivity of the LP analysis to changes in the fundamental frequency Fo and to noise. The method is well suited for combination with the Spectral Transform LP method, previously proposed by the authors [1].