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Recent studies emphasize the need of document context in human evaluation ofmachine translations, but little research has been done on the impact of userinterfaces on annotator productivity and the reliability of assessments. Inthis work, we compare human assessment data from the last two WMT evaluationcampaigns collected via two different methods for document-level evaluation.Our analysis shows that a document-centric approach to evaluation where theannotator is presented with the entire document context on a screen leads tohigher quality segment and document level assessments. It improves thecorrelation between segment and document scores and increases inter-annotatoragreement for document scores but is considerably more time consuming forannotators.

On User Interfaces for Large-Scale Document-Level Human Evaluation of Machine Translation Outputs