15. The computer implemented method of claim 12 , wherein the selecting includes searching for one of the plurality of refined rich context model sequences that has a shortest distance to the guiding sequence based on spectrum, pitch, and duration information of each sequence.
12. A computer implemented method, comprising: under control of one or more computing systems configured with executable instructions, refining a plurality of rich context models based on decision tree-tied Hidden Markov Models (HMMs) to produce a plurality of refined rich context models; performing pre-selection to compose a rich context model candidate sausage for an input text, the candidate sausage including a plurality of refined rich context model sequences, each sequence including at least some refined rich context models from the plurality of refined rich context models; selecting one of the plurality of refined rich context model sequences that has a least divergence from a guiding sequence that is obtained from the decision tree-tied HMMs; and generating output speech for the input text based at least on a rich context model sequence that is selected from the plurality of refined rich context model sequences.