Speech enhancement based on the subspace method

Abstract

A method of speech enhancement using microphone-array signal processing based on the subspace method is proposed and evaluated. The method consists of the following two stages corresponding to the different types of noise. In the first stage, less-directional ambient noise is reduced by eliminating the noise-dominant subspace. It is realized by weighting the eigenvalues of the spatial correlation matrix. This is based on the fact that the energy of less-directional noise spreads over all eigenvalues while that of directional components is concentrated on a few dominant eigenvalues. In the second stage, the spectrum of the target source is extracted from the mixture of spectra of the multiple directional components remaining in the modified spatial correlation matrix by using a minimum variance beamformer. Finally, the proposed method is evaluated in both a simulated model environment and a real environment.