Abstract: A pattern recognition system and method for optimal reduction of redundancy and size of a weighted and labeled graph presents receiving speech signals, converting the speech signals into word sequence, interpreting the word sequences in a graph where the graph is labeled with word sequences and weighted with probabilities and determinizing the graph by removing redundant word sequences. The size of the graph can also be minimized by collapsing some nodes of the graph in a reverse determinizing manner. The graph can further be tested for determinizability to determine if the graph can be determinized. The resulting word sequence in the graph may be shown in a display device so that recognition of speech signals can be demonstrated.

Abstract: A language recognition methodology is provided whereby any finite-state model of context may be used in a very general class of decoding cascades, and without requiring specialized decoders or full network expansion. The methodology includes two fundamental improvements: (1) a simple generalization, weighted finite-state transducers, of existing network models, and (2) a novel on-demand execution technique for network combination. With the methodology of the invention one or more of the network cascades are formulated as a finite state transducer, and is composed, for a selected portion of the network, with a next successively higher level of the network cascade to prescribe a mapped portion of that next successively higher level corresponding to the portion of the network cascade selected to be expanded.

Abstract: A pattern recognition system and method for optimal reduction of redundancy and size of a weighted and labeled graph presents receiving speech signals, converting the speech signals into word sequences, interpreting the word sequences in a graph where the graph is labeled with word sequences and weighted with probabilities and determinizing the graph by removing redundant word sequences. The size of the graph can also be minimized by collapsing some nodes of the graph in a reverse determinizing manner. The graph can further be tested for determinizability to determine if the graph can be determinized. The resulting word sequence in the graph may be shown in a display device so that recognition of speech signals can be demonstrated.

Abstract: A system and method for compiling weighted context-dependent rewrite rules into weighted finite-state transducers introduces context marking symbols only when and where they are needed. In particular, the compiler and compiling method use a composition of five simple finite-state transducers generated from a weighted context-dependent rewrite rule to represent that rule. An "r" finite-state transducer is generated from the right context portion .rho. of the weighted context-dependent rewrite rule. An "f" finite-state transducer is generated from the rewritten portion .phi. of the weighted context-dependent rewrite rule. A "Replace" finite-state transducer is generated from the rewritten and replacement portions .phi. and .psi. of the weighted context-dependent rewrite rule. Finally, "l.sub.1 " and "l.sub.2 " finite-state transducers are generated from the left context portion .lambda. of the weighted context-dependent rewrite rule.