Speech enhancement through nonlinear adaptive source separation methods

A new method that exploits the ideas of independent source separation in the context of speech enhancement in single sensor signals, is developed and tested in various situations. The channel distortions of the two sensor case are artificially reproduced by suitable linear and nonlinear filters. Separation is implemented via a Lagrange neural network. Results on speech signals are shown.