Filter bank design based on minimization of individual aliasing terms for minimum mutual information subband adaptive beamformin

This paper presents new filter bank design methods for subband adaptive beamforming. In this work, we design analysis and synthesis prototypes for modulated filter banks so as to minimize each aliasing term individually. We then drive the total response error to null by constraining these prototypes to be Nyquist(M) filters. Thereafter those modulated filter banks are applied to a speech separation system which extracts a target speech signal. In our system, speech signals are first transformed into the subband domain with our filter banks, and the subband components are then processed with a beamforming algorithm. Following beamforming, post-filtering and binary masking are further performed to remove residual noises. We show that our filter banks can suppress the residual aliasing distortion more than conventional ones. Furthermore, we demonstrate the effectiveness of our design techniques through a set of automatic speech recognition experiments on the multi-channel speech ...

• Type: Conference
• Year: 2008
• Where: ICASSP
• Authors: Ken'ichi Kumatani, John W. McDonough, S. Schachl, Dietrich Klakow, Philip N. Garner, Weifeng Li
• Keywords: ICASSP 2008, Modulated filter Banks, Signal Processing, Speech Signals, filter Banks