Speech signal recovery in white noise using an adaptive Kalman filter

This paper deals with the problem of Adaptive Noise Cancellation (ANC) when only a corrupted speech signal with an additive Gaussian white noise is available for processing. All the approaches based on the Kalman filter proposed in the past, in this context, operate in two steps: they first estimate the noise variances and the parameters of the signal model and secondly estimate the speech signal. We propose a new method to estimate the noise variances. This estimation is made by reformulating and adapting the Mehra approach.