17. A method for training tree transducers for probabilistic operations, the method comprising: using a computer to obtain information in the form of a first-tree, second information corresponding to said first tree, and transducer information; and using said computer to automatically distill information from said first tree, from said second information, and from said transducer information into a list of information in a specified tree grammar with weights associated with entries in the list and to produce locally optimal weights for said entries.
17. A method for training tree transducers for probabilistic operations, the method comprising: using a computer to obtain information in the form of a first-tree, second information corresponding to said first tree, and transducer information; and using said computer to automatically distill information from said first tree, from said second information, and from said transducer information into a list of information in a specified tree grammar with weights associated with entries in the list and to produce locally optimal weights for said entries. 18. A method as in claim 17 , wherein said automatically distill comprises observing when a specified rule in said list of information is used, and increasing said weight associated with said specified rule when said specified rule is used.