  In the last years there has been a growing interest for nonlinear speech
models. Several works have been published revealing the better performance of
nonlinear techniques, but little attention has been dedicated to the
implementation of the nonlinear model into real applications. This work is
focused on the study of the behaviour of a combined linear/nonlinear predictive
model based on linear predictive coding (LPC-10) and neural nets, in a speech
waveform coder. Our novel scheme obtains an improvement in SEGSNR between 1 and
2.5 dB for an adaptive quantization ranging from 2 to 5 bits.
