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SRI has developed a new architecture for integrating speech and natural-language processing that applies linguistic constraints during recognition by incrementally expanding the state-transition network embodied in a unification grammar. We compare this dynamic-grammar-network (DGN) approach to its principal alternative, word-lattice parsing, presenting preliminary experimental results that suggest the DGN approach requires much less computation time than word-lattice parsing, while maintaining a very tractable recognition search space.
Moore et al. (Sun,) studied this question.