 Every level "i" of the LHMM consists of "K""i" HMMs running in parallel.LHMMs are sometimes useful in specific structures because they can facilitate learning and generalization.For example, even though a fully connected HMM could always be used if enough training data were available, it is often useful to constrain the model by not allowing arbitrary state transitions.