1. A method for generating an embedded couple hidden Markov model, comprising: obtaining data of two or more dimensions, the data having a label representing a known pattern; segmenting the data uniformly into one or more super segments; assigning each super segment to a super state of a super channel in a coupled hidden Markov model at a super layer of an embedded coupled hidden Markov model, the super layer having at least one super channel; segmenting each super segment into lower layer segments, each of which corresponds to a lower layer state of a lower channel of a lower layer coupled hidden Markov model associated with one of the super states; optimally segmenting the data at the lower layer to produce an optimal segmentation; updating one or more parameters of at least one model associated with at least one lower layer state based on the optimal segmentation; and updating one or more parameters of at least one model associated with at least one super state based on the at least one model associated with the at least one lower layer state to generate an embedded coupled hidden Markov model modeling the known pattern.