MMSE-OPTIMAL COMBINATION OF WIENER FILTERING AND HARMONIC MODEL BASED SPEECH ENHANCEMENT IN A GENERAL FRAMEWORK

摘要

For the reduction of additive acoustic noise, various methods and clean speech estimators are available, with specific strengths and weaknesses. In order to combine the strengths of two such approaches, we derive a minimum mean squared error (MMSE)-optimal estimator of the clean speech given two independent initial clean speech estimates. As an example we present a specific combination that results in a weighted mixture of the Wiener filter and a simple, low-cost harmonic speech model. The proposed estimator benefits from the additional information provided by the harmonic model, leading to a better protection of harmonic components of voiced speech as compared to the traditional Wiener filter. Instrumental measures predict improvements in speech quality and speech intelligibility for the proposed combination over each individual estimator.