F-structure transfer-based statistical machine translation
Graham, Yvette and van Genabith, Josef and Bryl, Anton (2009) F-structure transfer-based statistical machine translation. In: Lexical Functional Grammar 2009, 13-16 July 2009, Cambridge, UK.
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In this paper, we describe a statistical deep syntactic transfer decoder that is trained fully automatically on parsed bilingual corpora. Deep syntactic transfer rules are induced automatically from the f-structures of a LFG parsed bitext corpus by automatically aligning local f-structures, and inducing all rules consistent with the node alignment. The transfer decoder outputs the n-best TL f-structures given a SL f-structure as input by applying large numbers of transfer rules and searching for the best output using a
log-linear model to combine feature scores. The decoder includes a fully integrated dependency-based tri-gram language model. We include an experimental evaluation of the decoder using different parsing disambiguation
resources for the German data to provide a comparison of how the system performs with different German training and test parses.
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