Continuously adaptive linear predictive coding of speech

A continuously adaptive approach to speech encoding is presented. In contrast with other adaptation methods, it provides reliable modeling of the transition between two phonemes, and, unlike the usual block-stationary techniques, it eliminates the need to detect these transitions. Continuously adaptive linear predictive coding takes into account the inherent nonstationarity of the speech signal by using the expected minimum rate of change of the model parameters as a constraint in the recursive estimation of these parameters. The criterion considered is a constrained-least-squares cost functional which incorporates with equal weight all instantaneous errors up to the time of observation. An appropriate algorithm is given, and simulations are presented to illustrate the basic cost-performance tradeoffs involved in the approach