1. A method for compiling a plurality of linear rules created by machine learning for use in natural language processing, the method comprising: compiling a respective transducer for each one of a plurality of types of rules obtained by partitioning a plurality of linear rules; creating a combined finite state transducer from a union of the respective transducers compiled from the plurality of linear rules; and processing natural language speech using the combined finite state transducer.
1. A method for compiling a plurality of linear rules created by machine learning for use in natural language processing, the method comprising: compiling a respective transducer for each one of a plurality of types of rules obtained by partitioning a plurality of linear rules; creating a combined finite state transducer from a union of the respective transducers compiled from the plurality of linear rules; and processing natural language speech using the combined finite state transducer. 7. The method of claim 1 , further comprising: applying an input to the combined finite state transducer; searching for a best path for the input with respect to the finite state transducer; and determining a best classification result based on the best path.