Parametric multichannel noise reduction algorithm utilizing temporal correlations in reverberant environment

In this paper, we propose a parametric multichannel noise reduction algorithm utilizing temporal correlations in a noisy and reverberant environment. Under the reverberant condition, the received acoustic signal becomes highly correlated in the time domain and it makes successful noise reduction quite difficult. The proposed parametric noise reduction method takes account of interdependencies between components observed from different frames. Extended speech and noise power spectral density (PSD) matrices are estimated containing additional temporal information, and the parametric multichannel noise reduction filter based on these PSD matrices is applied to the input microphone array signal. According to the experimental results, the proposed algorithm has been found to show better performances compared with the conventional multiplicative filtering technique which considers the current input signals only.