The paper defines weighted head transducers, finite-state machines that perform middle-out string transduction. These transducers are strictly more expressive than the special case of standard left-to-right finite-state transducers. Dependency transduction models are then defined as collections of weighted head transducers that are applied hierarchically. A dynamic programming search algorithm is described for finding the optimal transduction of an input string with respect to a dependency transduction model. A method for automatically training a dependency transduction model from a set of input-output example strings is presented. The method first searches for hierarchical alignments of the training examples guided by correlation statistics, and then constructs the transitions of head transducers that are consistent with these alignments. Experimental results are given for applying the training method to translation from English to Spanish and Japanese.
We report on the initial stages of development of a robust parsing system, to be used as part of The Editor's Assistant, a program that detects and corrects textual errors and infelicities in the area of syntax and style. Our mechanism extends the standard PATR-n formalism by indexing the constraints on rules and abstracting away control of the application of these constraints. This allows independent specification of grouping and ordering of the constraints, which can improve the efficiency of processing, and in conjunction with information specifying whether constraints are necessary or optional, allows detection of syntactic errors. Chicago Press, Chicago, Illinois. H Uszkoreit [1990] Strategies for Adding Control Information to Declarative Grammars. In Proceedings of the 29th Annual Meeting of the Association for Computational Linguistics, pp237-245, R M Weischedcl and J E Black [1980] Responding Intelligently to Unparsable Inputs.
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