 Finally, a different rationale towards addressing the problem of modeling nonstationary data by means of hidden Markov models was suggested in 2012.It consists in employing a small recurrent neural network (RNN), specifically a reservoir network, to capture the evolution of the temporal dynamics in the observed data.This information, encoded in the form of a high-dimensional vector, is used as a conditioning variable of the HMM state transition probabilities.