Neural speech enhancement using dual extended Kalman filtering

The removal of noise from speech signals has applications ranging from speech enhancement for cellular communications, to front ends for speech recognition systems. Spectral techniques are commonly used in these applications, but frequently result in audible distortion of the signal. A nonlinear time-domain method called dual extended Kalman filtering (DEKF) is presented that demonstrates significant advantages for removing nonstationary and colored noise from speech.