Speech enhancement using spectral envelope side information

This paper proposes several methods for noise reduction using deterministic side information about the desired signal as a constraint on the reconstruction. Two forms of side information are considered separately: short-time linear predictive coefficients, and short-time zero-phase impulse response coefficients. We derive general expressions for the ML, MAP and MMSE estimators, and develop algorithms that yield the ML estimators with the above side information for speech corrupted by additive white Gaussian noise. We also explore the use of these methods in the traditional noise reduction problem with no side information.