2014 · 87 citations · 14 references
ComputingComputer ScienceComputational LinguisticsFeature EngineeringNatural Language ProcessingLanguage ModelingLanguage ModelsMachine TranslationRelevance RankingText Feature EngineeringText SummarizationEvaluationEvaluation Of Ranking ModelsFeature-based Ranking ModelsMetricsRanking EvaluationRanking FeaturesRanking ModelsTrec Evaluation
We present the UvA-ILLC submission of the BEER metric to WMT 14 metrics task. BEER is a sentence level metric that can incorporate a large number of features combined in a linear model. Novel con-tributions are (1) efficient tuning of a large number of features for maximizing corre-lation with human system ranking, and (2) novel features that give smoother sentence level scores. 1
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Engineering, Computer Engineering, Electrical Engineering +17
(Meta-) evaluation of machine translation
Chris Callison-Burch, Cameron Shaw Fordyce, Philipp Koehn et al. · 2007 · 385 citations · Full text
Humanities, French, Spanish +14