A generalized perceptual time-frequency subtraction method for speech enhancement

This paper presents a new speech enhancement scheme to meet the strong demand for quality noise reduction at very low signal-to-noise ratios (SNR). The proposed method generalizes the spectral subtraction algorithm to correlate time-frequency domain information based on the auditory masking property. The psycho acoustic model is integrated with the unvoiced speech enhancement algorithm to improve the intelligibility of speech. The proposed perceptual wavelet transform has successfully resolved the frequency and temporal components of speech signal. Auditory masking of noise is modeled by thresholding wavelet transform coefficients with adaptive suppression of different types of noise and distortion. Rigorous performance evaluations show that the proposed system is capable of reducing noise with little speech degradation in adverse noise environments and the perceptual speech quality is superior than several competitive methods