A SIGNAL-SEPARATION-BASED ARRAY POSTFILTER FOR DISTANT SPEECH RECOGNITION

In standard microphone array processing for distant speech recognition, the beamformed output is postfiltered to reduce residual noise. Postfiltering is usually performed through a Weiner filter whose parameters are estimated from both the beamformer output and the signals captured at the microphones themselves. Conventional postfiltering methods assume diffuse or incoherent noise at the various microphones in order to estimate these parameters. When the noise does not conform to this assumption they perform poorly. We propose an alternate postfiltering mechanism that attenuates noise by estimating and separating out the contributions of speech and noise explicitly. Experiments on a corpus of in-car two-channel recordings show that the proposed postfiltering algorithm outperforms conventional postfilters significantly under many noise conditions

A SIGNAL-SEPARATION-BASED ARRAY POSTFILTER FOR DISTANT SPEECH RECOGNITION

In standard microphone array processing for distant speech recognition, the beamformed output is postfiltered to reduce residual noise. Postfiltering is usually performed through a Weiner filter whose parameters are estimated from both the beamformer output and the signals captured at the microphones themselves. Conventional postfiltering methods assume diffuse or incoherent noise at the various microphones in order to estimate these parameters. When the noise does not conform to this assumption they perform poorly. We propose an alternate postfiltering mechanism that attenuates noise by estimating and separating out the contributions of speech and noise explicitly. Experiments on a corpus of in-car two-channel recordings show that the proposed postfiltering algorithm outperforms conventional postfilters significantly under many noise conditions