Isolated word recognition using a Liquid State Machine
David Verstraeten, Benjamin Schrauwen, Dirk Stroobandt · 2005
An implementation of the recently proposed concept of the Liquid State Machine using a Spiking Neural Network (SNN) is trained to perform isolated word recognition. We investigate two di#erent speech front ends and di#erent ways of coding the inputs into spike trains. The robustness against noise added to the speech is also briefly researched. It turns out that a biologically realistic configuration of the LSM gives the best result, and that it performs very well for the task of speech recognition.