Speech restoration from LPC parameters corrupted by channel noise - Premkumar, Annamalai Benjamin (2020)
Restoration of speech parameters that have been degraded by noisy channel is of paramount importance, since mutilated speech parameters such as linear predictive coefficients (LPC) may render speech totally irrecoverable. The paper provides a technique using discrete dyadic wavelet transforms as a preprocessing stage prior to LPC extraction. We show that this step makes the speech parameters more robust to noise perturbation in the channel and hence makes recovery of speech possible. We discuss the effects of applying a single level and a three level transformation to speech prior to compression and compare the quality of recovered speech in both cases. We also apply a Wiener filter to the wavelet coefficients and show that the recovered speech is of appreciable quality.