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Computational Linguistics

Paola Merlo, Editor
September 2008, Vol. 34, No. 3, Pages 391-427
(doi: 10.1162/coli.2008.07-051-R2-03-57)
© 2008 Massachusetts Institute of Technology
Training Tree Transducers
Article PDF (773.45 KB)
Abstract

Many probabilistic models for natural language are now written in terms of hierarchical tree structure. Tree-based modeling still lacks many of the standard tools taken for granted in (finite-state) string-based modeling. The theory of tree transducer automata provides a possible framework to draw on, as it has been worked out in an extensive literature. We motivate the use of tree transducers for natural language and address the training problem for probabilistic tree-to-tree and tree-to-string transducers.