• use Gaussian mixture densities to represent state output distribution

• each mixture component is a multivariate Gaussian distribution

• the essential problem is to estimate the means and variances of an HMM in which each state output distribution consists of multiple Gaussian mixture components

• full likelihood of each observation sequence is based on the summation of all possible state sequence

• each observation is assigned to every state in proportion to the state occupancy probability