- 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