**Download:**
Poster.

“Efficient Path
Counting Transducers for Minimum Bayes-Risk Decoding of Statistical
Machine Translation Lattices”
by G. Blackwood, A. de Gispert, and W. Byrne.
In *Proceedings of the Annual Meeting of the Association for
Computational Linguistics -- Short Papers*, 2010, pp. 27-32 (6 pages).

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.

**Download:**
Poster.

**BibTeX entry:**

@inproceedings{pathcountacl2010, author = {G. Blackwood and A. de Gispert and W. Byrne}, title = {Efficient Path Counting Transducers for Minimum {B}ayes-Risk Decoding of Statistical Machine Translation Lattices}, booktitle = {Proceedings of the Annual Meeting of the Association for Computational Linguistics -- Short Papers}, pages = {27--32 (6 pages)}, year = {2010}, url = {http://www.aclweb.org/anthology/P/P10/P10-2006.pdf} }

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