A kalman filter with a perceptual post-filter to enhance speech degraded by colored noise

Ning Ma, Martin Bouchard, Rafik A. Goubran

Abstract


A method for colored noise speech enhancement based on a Kalman filter combined with a post-filter using masking properties of human auditory systems was presented. Time domain forward masking effects and frequency domain simultaneous masking properties were considered in the post-filter. A colored noise v(n), used as the noise source, was obtained by running a white noise signal through an AR filter. It was found that the new method has the best performance for any input noisy speech signal-to-noise ratio value.

Keywords


Algorithms; Computer simulation; Matrix algebra; Parameter estimation; Signal processing; Signal to noise ratio; Speech intelligibility; Speech processing; Vectors; White noise; Colored noises; Speech degradation; Speech enhancement algorithms; Speech signals

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