Acoustic echo and noise cancellation using Kalman filter in a modified GSC framework

In this paper a novel method for acoustic echo and noise cancellation in a generalized sidelobe canceler framework is described. The primary contribution of this work is the development of multichannel adaptive Kalman filter (MCAKF) in a modified generalized sidelobe canceler (MGSC) framework. Additionally, in this work both the near end speech signal and noise is assumed to be unknown. In the proposed method speech acquired by a microphone array is subject to adaptive beamforming using MVDR method. On the other hand a blocking matrix filter is used to attenuate the near end speech signal while passing both the noise and residual echo. A MCAKF is developed in this context to also estimate the noise and residual echo. Hence, a difference of MCAKF output and the adaptive beamformer (ABF) output gives an estimate of the near end speech signal. The performance of proposed method is evaluated using subjective and objective measures on the ARCTIC database. Distant speech recognition experiments are also conducted on the ARCTIC database. The proposed method gives reasonable improvements both in terms of perceptual evaluation and distant speech recognition.