Speech enhancement based on Kalman filtering and EM algorithm

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.<
>