Shallow surfacelevel metrics, such as BLEU and TER (Papineni et al., 2002;Snover et al., 2006), still predominate in practice, due in part to their reasonable correlation to human judgements, and their being parameter free, making them easily portable to new languages.
trained metrics (Song and Cohn, 2011;Stanojevic and Sima'an, 2014;Ma et al., 2017;Shimanaka et al., 2018), which are learned to match human evaluation data, have been shown to result in a large boost in performance.