Iterative speech enhancement with spectral constraints

Abstract

A new and improved iterative speech enhancement technique based on spectral constraints is presented in this paper. The iterative technique, originally formulated by Lim and Oppenheim, attempts to solve for the maximum likelihood estimate of a speech waveform in additive white noise. The new approach applies inter- and intra-frame spectral constraints to ensure convergence to reasonable values and hence improve speech quality. An extremely efficient technique for applying these constraints is in the use of line spectral pair (LSP) coefficients. The inter-frame constraints ensures more speech-like formant trajectories than those found in the unconstrained approach. Results from speech degraded by additive white Gaussian noise show noticeable quality improvement.