Improving AMBER, an MT Evaluation Metric

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Proceedings titleNAACL 2012 Workshop on Statistical Machine Translation: (WMT-2012)
Conference7th Workshop on Statistical Machine Translation (WMT 2012), June 7-8, 2012, Montréal, QC, Canada
Pages5963; # of pages: 5
AbstractA recent paper described a new machine translation evaluation metric, AMBER. This paper describes two changes to AMBER. The first one is incorporation of a new ordering penalty; the second one is the use of the downhill simplex algorithm to tune the weights for the components of AMBER. We tested the impact of the two changes, using data from the WMT metrics task. Each of the changes by itself improved the performance of AMBER, and the two together yielded even greater improvement, which in some cases was more than additive. The new version of AMBER clearly outperforms BLEU in terms of correlation with human judgment.
Publication date
AffiliationInformation and Communication Technologies; National Research Council Canada
Peer reviewedYes
NPARC number20255954
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Record identifiera0fb52ca-4e0d-49b5-9ba8-e34401cc787d
Record created2012-07-07
Record modified2016-05-09
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