Speech Enhancement with Geometric Advent of Spectral Subtraction using Connected Time-Frequency Regions Noise Estimation
Nasir Saleem, Sher Ali, Usman A. Khan, Farman Ullah · Research Journal of Applied Sciences Engineering and Technology · 2013
Speech enhancement with Geometric Advent of Spectral subtraction using connected time-frequency regions noise estimation aims to de-noise or reduce background noise from the noisy speech for better quality, pleasantness and improved intelligibility. Numerous enhancement methods are proposed including spectral subtraction, subspace, statistical with different noise estimations. The traditional spectral subtraction techniques are reasonably simple to implement and suffer from musical noise. This study addresses the new approach for speech enhancement which has minimized the insufficiencies in traditional spectral subtraction algorithms using MCRA. This approach with noise estimation has been evolved with PESQ, the ITU-T standard; Frequency weighted segmental SNR and weighted spectral slope. The analysis shows that Geometric approach with time-frequency connected regions has improved results than old-fashioned spectral subtraction algorithms. The normal hearing tests has suggested that new approach has lower audible musical noise.