Robust LPC analysis and synthesis using the KL transformation of acoustic subwords spectra

The authors propose a novel approach to the modeling and estimation of the speech spectral envelope over acoustic subwords that exhibits robust performance in noise. The technique exploits the underlying signal structure of speech to improve parameter estimates, and it uses the perceptual properties of hearing to decrease the computational requirements in a perceptually meaningful way. The approach provides a considerable speech quality improvement over other methods