Impulsive noise cancellation for speech enhancement using state space adaptive algorithm
Rashmirekha Ram, Sarthak Panda, Hemanta Kumar Palo, Mihir Narayan Mohanty · 2016
The occurrence of noise in almost all types of signals is natural. Though the noise variants are many, the impulsive noise in signal highly affects its quality. In this piece of work, speech signal is considered for enhancement that is contaminated with impulsive noise. Generally, hiccups create such type of noise due to tiredness or myoclonic problem of human subjects. Removal of this type of impulsive noise can enhance the speech signal and can be used in case of recognition, security and in the field of medicine. The popular recursive least mean square (RLS) algorithm has been used for this purpose. Also the state space variant of RLS (SSRLS) application enhances the result and can be used for real time applications. The result shows its performance in terms of signal to noise ratio (SNR) and the visualization of the speech signal.