A decoder for probabilistic synchronous tree insertion grammars

Authors:
Steve DeNeefe;Kevin Knight;Heiko Vogler
Affiliations:
USC Information Sciences Institute, Marina del Rey, CA;USC Information Sciences Institute, Marina del Rey, CA;Technische Universität Dresden, Dresden
Venue:
ATANLP '10 Proceedings of the 2010 Workshop on Applications of Tree Automata in Natural Language Processing
Year:
2010

Citing 17
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Abstract

Synchronous tree insertion grammars (STIG) are formal models for syntax-based machine translation. We formalize a decoder for probabilistic STIG; the decoder transforms every source-language string into a target-language tree and calculates the probability of this transformation.