A Speech Enhancement Method Based on Kalman Filtering

The enhancement of speech degraded by non-stationary interferers is a highly relevant and difficult task for many signal processing applications. In this study, we present a monaural speech enhancement method based on spectral subtraction and Kalman filtering (KF) by extracting the Liljencrants–Fant (LF) excitation during voiced speech, in which the nature of glottal flow can be maintained. Therefore, the approach could preserve the glottal pulse's nature characteristic in Kalman filtering and thus achieve significant improvements on objective quality. The quality of the enhanced speech has been evaluated by perceptual evaluation of speech quality (PESQ) score. The results indicate that the proposed algorithm could improve the output speech quality compared with the conventional KF algorithm and sub-band spectral subtraction.