Efficient path counting transducers for minimum bayes-risk decoding of statistical machine translation lattices

Authors:
Graeme Blackwood;Adrià de Gispert;William Byrne
Affiliations:
Machine Intelligence Laboratory, U.K.;Machine Intelligence Laboratory, U.K.;Machine Intelligence Laboratory, U.K.
Venue:
ACLShort '10 Proceedings of the ACL 2010 Conference Short Papers
Year:
2010

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Abstract

This paper presents an efficient implementation of linearised lattice minimum Bayes-risk decoding using weighted finite state transducers. We introduce transducers to efficiently count lattice paths containing n-grams and use these to gather the required statistics. We show that these procedures can be implemented exactly through simple transformations of word sequences to sequences of n-grams. This yields a novel implementation of lattice minimum Bayes-risk decoding which is fast and exact even for very large lattices.