Title :
Speech enhancement based on Kalman filtering and EM algorithm
Author :
Du, Weixiu ; Driessen, P.
Author_Institution :
Dept. of Electr. & Comput. Eng., Victoria Univ., BC, Canada
Abstract :
Speech enhancement via Kalman filtering is considered. It is generally agreed that the quality of the estimate of speech production model parameters is crucial to the performance of the Kalman filter. The Kalman filter with a more accurate estimate of the LPC parameters will generally achieve better noise cancellation results. In practice only the noisy speech is available for the LPC analysis. Then the estimate of the LPC parameters is usually inaccurate, which in turn degrades the performance of the Kalman filter. In order to overcome the problem, a Kalman filtering scheme applied in conjunction with the EM algorithm is proposed. Simulation results demonstrate the expected performance improvement in terms of signal-to-noise ratio (SNR) gains by the new method
Keywords :
Kalman filters; encoding; filtering and prediction theory; speech analysis and processing; Kalman filter; Kalman filtering; LPC analysis; LPC parameters; SNR gains; noise cancellation; noisy speech; signal-to-noise ratio; simulation results; speech enhancement; speech production model parameters; Filtering algorithms; Kalman filters; Linear predictive coding; Noise cancellation; Nonlinear filters; Speech analysis; Speech enhancement; Speech processing; White noise; Wiener filter;
Conference_Titel :
Communications, Computers and Signal Processing, 1991., IEEE Pacific Rim Conference on
Conference_Location :
Victoria, BC
Print_ISBN :
0-87942-638-1
DOI :
10.1109/PACRIM.1991.160701