Has Machine Translation Achieved Human Parity? A Case for Document-level Evaluation
Samuel Läubli, Rico Sennrich, Martin Volk · 2018
Recent research suggests that neural machine translation achieves parity with professional human translation on the WMT Chinese-English news translation task.We empirically test this claim with alternative evaluation protocols, contrasting the evaluation of single sentences and entire documents.In a pairwise ranking experiment, human raters assessing adequacy and fluency show a stronger preference for human over machine translation when evaluating documents as compared to isolated sentences.Our findings emphasise the need to shift towards document-level evaluation as machine translation improves to the degree that errors which are hard or impossible to spot at the sentence-level become decisive in discriminating quality of different translation outputs.