Multichannel parametric speech enhancement

We present a parametric model-based multichannel approach for speech enhancement. By employing an autoregressive model for the speech signal and using a trained codebook of speech linear predictive coefficients, minimum mean square error estimation of the speech signal is performed. By explicitly accounting for steering errors in the signal model, robust estimates are obtained. Experiments show that the proposed method results in significant performance gains.