Spectral subtraction based on the structure of noise power spectral density

This paper proposes a novel spectral subtraction algorithm based on the structure of noise power spectral density,which will be herein referred as NPSD-SS,for reducing musical noise without introducing audible speech distortion. First,we propose an adaptive averaging periodogram based on the structure of the noise spectrum,which will be referred NPSD-AAP,where the better performance of the NPSD-SS is achieved mainly due to that the proposed NPSD-AAP provides a low-variance and adaptive-bandwidth spectral estimator.Second,the maximum noise reduction is adaptively determined by the property of the noise spectrum to further suppress the non-continuous noise components. Objective tests show that the NPSD-SS is better than the CSS in terms of the SNR improvement and the amount of noise reduction.Informal listening tests further confirm the validity of the proposed NPSD-SS.