namic probability values as before. New input would be requested from the user and the process described above would be repeated until the point where paths are sought to be determined. The last path of the marked tree nodes from the root to the leaf which was successful in the previous execution of the method is checked to determine whether one or more possible connections can be made from the last successful path to the marked nodes from current utterance, i.e., we seek to determine whether or not the marked tree nodes of the current utterance can be reached from a higher node other than the root of the past successful path. If such connection(s) can be made nodes are then marked on the previously successful path between the root and the connection point as nodes in the path(s) under consideration. The method is resumed and executed as described above.
With respect to FIG. 2, in implementation, a random access memory can store the predetermined numeric representations of recognizable words. Alternate embodiments might use EPROM, ROM, EEPROM, magnetic tape, CD-ROM or other means for storing data. Input speech 2-1 might be uttered into a microphone coupled to a general purpose digital computer to perform speech recognition 2-2 and the computations necessary to effectuate the aforementioned method. Other input sources could include a keyboard, mouse or pointing device, handwriting recognition devices, facsimile machines, optical character recognition software or devices, or output from a computer program, which might be directly coupled into the invention without the need for speech recognition, as shown in FIG. 2 by the broken line identified by reference numeral 2-3. Other computer means for computing might be employed, such as a digital signal processor for instance.
FIG. 9 is a source code listing of the NAWK programming language implementation of the construction of the data structures of FIGS. 4 and 5 as well as determining all paths in user utterances.
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