Minimum Bayes risk decoding for BLEU
Abstract
We present a Minimum Bayes Risk (MBR) decoder for statistical machine
translation. The approach aims to minimize the expected loss of translation errors with
regard to the BLEU score. We show that MBR decoding on N-best lists leads to an
improvement of translation quality. We report the performance of the MBR decoder on four
different tasks: the TC-STAR EPPS Spanish-English task 2006, the NIST Chinese-English
task 2005 and the GALE Arabic-English and Chinese-English task 2006. The absolute
improvement of the BLEU score is between 0.2% for the TC-STAR task and 1.1% for the
GALE Chinese-English task.