6. A method for training acoustic model, comprising: a training respective speech unit in a speech database to generate an acoustic model, the speech unit includes acoustic parameters and context labels; for context combination, performing a decision tree clustering process to generate the acoustic model with a decision tree; determining fuzzy data in the speech database based on the acoustic model with the decision tree; generating the fuzzy context feature labels for the fuzzy data; and cluster training the speech database based on the fuzzy context feature labels to generate the acoustic model with the fuzzy decision tree, using a device selected from the group consisting of a computer and a logic circuit.
7. The method according to claim 6 , wherein the step of determining the fuzzy data further comprises: estimating the speech unit; determining a degree to which candidate context labels of the speech unit fall into a category; and determining the speech unit as the fuzzy data if the degree satisfies a predetermined threshold.