Incremental hypothesis alignment with flexible matching for building confusion networks: BBN system description for WMT09 system combination task

Authors:
Antti-Veikko I. Rosti;Bing Zhang;Spyros Matsoukas;Richard Schwartz
Affiliations:
BBN Technologies, Cambridge, MA;BBN Technologies, Cambridge, MA;BBN Technologies, Cambridge, MA;BBN Technologies, Cambridge, MA
Venue:
StatMT '09 Proceedings of the Fourth Workshop on Statistical Machine Translation
Year:
2009

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Abstract

This paper describes the incremental hypothesis alignment algorithm used in the BBN submissions to the WMT09 system combination task. The alignment algorithm used a sentence specific alignment order, flexible matching, and new shift heuristics. These refinements yield more compact confusion networks compared to using the pair-wise or incremental TER alignment algorithms. This should reduce the number of spurious insertions in the system combination output and the system combination weight tuning converges faster. System combination experiments on the WMT09 test sets from five source languages to English are presented. The best BLEU scores were achieved by combing the English outputs of three systems from all five source languages.