Echo Cancellation – Model-Based Approach
By using a new, model-based approach for modelling the acoustical environment [enzner06a] it is possible to employ the Kalman algorithm in the context of echo cancellation. In contrast to the traditional approach, the acoustical echo path is considered as a time-variable vectorial state variable. A stationary Markov model is assumed for this variable. The near-end speech input s represents an observation noise for the echo path.
The task of an acoustic echo controller is thus to exctract the observation noise from the microphone signal y in an optimal sense. The Kalman algorithm provides a possibility to estimate the paramters of a generalized Wiener filter. The two-stage filter stucture consists of an acoustic echo canceler between transmit and receive paths and a postfilter for residual echo suppression. In contrast to previous solutions, this filter stucture can be derived directly by following the MMSE criterion. The Kalman filter basically requires only three statistical parameters of the acoustic environment:
- the length of the echo path vector
- the degree of time-variability of the acoustic echo path, i.e., the time-constant of the vector Markov model of the echo path
- and the PSD of the observation noise at the hands-free microphone
A generalization of this theory in order to achieve combined acoustic echo and noise reduction, is straightforward. The Wiener postfilter needs to be extended to consider the PSDs of existing additive noise.