A psychoacoustic spectral subtraction method for noise suppression in automatic speech recognition

A time-frequency spectral subtraction method based on the knowledge of several psychoacoustic properties of human perception is presented. These effects are the critical band filtering, synaptic adaptation which also introduces temporal forward masking, equal loudness preemphasis, power law of hearing, and simultaneous masking effect. The perceptual speech and noise is estimated separately by a detailed psychoacoustic non-linear transformation undergoing in the human auditory system. The spectral subtraction using a over-subtraction factor and a spectral floor is measured by a speech recognition front-end using a continuous density HMM recognizer. The method shows reduced residual noise and improved word recognition performance in broadband Gaussian noise conditions compared to conventional spectral subtraction method.