Formant estimation by LPC with a new error criterion

In autoregressive coding of speech, it is essential that the LPC model contain accurate information about the first three formants; specifically, that the LPC spectrum should reproduce the correct formant frequencies and the corresponding bandwidths. We shall demonstrate that the modified linear predictive coder (MLPC) is superior to the widely used linear predictive coder (LPC) when the data frames are short. MLPC uses a new error criterion. Indeed, prediction is sought in terms of certain filtered signals obtained by passing the speech into a cascade of first order digital filters. The normal equations for this modified linear predictor are derived and a reversible window, suitable for this new formulation, is proposed. Application to speech is demonstrated.